diff --git a/add_dependent.py b/add_dependent.py index 6cf0e05..2dd7d8c 100644 --- a/add_dependent.py +++ b/add_dependent.py @@ -37,7 +37,9 @@ go_mod += "require (\n" # Add the dependencies for link in github_links: - go_mod += f" {link} v0.0.0\n" # replace "v0.0.0" with the actual version if known + # Remove http:// or https:// from the URL + link = link.replace('http://', '').replace('https://', '') + go_mod += f" {link} v0.0.0 // indirect\n" # replace "v0.0.0" with the actual version if known # End the require block go_mod += ")\n" diff --git a/github_links.txt b/github_links.txt index bb2856b..6ce70b3 100644 --- a/github_links.txt +++ b/github_links.txt @@ -1,552 +1,582 @@ -https://github.com/JianXu95/FedPAC -https://github.com/abhimanyudubey/private_federated_linear_bandits -https://github.com/google-research/federated/tree/master/optimization -https://github.com/NVlabs/FedFomo +https://github.com/maiph123/verticalgnn +https://github.com/insujeon/MetaVD +https://github.com/sparsefed/sparsefed https://github.com/cuhksz-nlp/GCASeg -https://github.com/giemp95/feddti -https://github.com/omarfoq/streaming-fl -https://github.com/ramshi236/Accelerated-Federated-Learning-Over-MAC-in-Heterogeneous-Networks -https://github.com/aelgabli/FedNew -https://github.com/alibaba/FederatedScope/tree/backdoor-bench -https://github.com/hit-mdc/FedTSC-FedST -https://github.com/morningD/FlexCFL -https://github.com/RamiHaf/Explainable-Federated-Learning-via-Random-Forests -https://github.com/luozhengquan/DFL -https://github.com/ElvisShaoYumeng/BLADE-FL -https://github.com/KaiyuanZh/FLIP -https://github.com/JiahuaDong/FISS -https://github.com/mmendiet/FedAlign -https://github.com/facebookresearch/dp_compression -https://github.com/FederalLab/OpenFed -https://github.com/MediaBrain-SJTU/FedDisco -https://github.com/omarfoq/knn-per +https://github.com/basiralab/Fed-CBT +https://github.com/unc-optimization/FedDR https://github.com/eth-sri/tableak +https://github.com/jinghuichen/focused-flip-federated-backdoor-attack +https://github.com/Princeton-SysML/GradAttack +https://github.com/google/fedjax +https://github.com/NVIDIA/NVFlare/tree/dev/research/fed-ce +https://github.com/dunchen/AsyncDrop__Release +https://github.com/CodePothunter/fednp +https://github.com/CodePothunter/fednp/blob/main/appendix.pdf +https://github.com/wyjeong/FedMatch +https://github.com/harliwu/fedamd +https://github.com/APPFL/APPFL +https://github.com/MingruiLiu-ML-Lab/Federated-Sparse-Learning +https://github.com/teijyogen/secsv +https://github.com/purp1eHaze/FedIPR +https://github.com/hangxu0304/DeepReduce +https://github.com/YangLiangwei/FeSoG +https://github.com/bdemo/pfedbred_public +https://github.com/epfml/federated-learning-public-code/tree/master/codes/FedDF-code +https://github.com/google-research/federated/tree/master/distributed_dp +https://github.com/FederatedAI/research +https://github.com/yzhao062/anomaly-detection-resources +https://github.com/Soptq/iccv23-3sfc +https://github.com/zhanghangtao/poisoning-attack-on-fl +https://github.com/WenkeHuang/RethinkFL +https://github.com/tsingz0/fedala +https://github.com/lx10077/fedavgpy https://github.com/Xtra-Computing/FedTree -https://github.com/sunjunaimer/TPAMI-LAQ -https://github.com/alibaba/FederatedScope/tree/FSreal -https://github.com/xqlin98/Fair-yet-Equal-CML -https://github.com/VITA-Group/MaT-FL -https://github.com/illidanlab/FADE -https://github.com/DianboWork/FedDS -https://github.com/varnio/fedsim -https://github.com/zfan20/PFGNNPlus -https://github.com/rdz98/fedrecattack -https://github.com/Accenture/Labs-Federated-Learning -https://github.com/LiruichenSpace/FedFusion -https://github.com/nusdbsystem/falcon -https://github.com/hongliny/sharp-bounds-for-fedavg-and-continuous-perspective -https://github.com/WeiNingChen/pbm -https://github.com/FuChong-cyber/label-inference-attacks -https://github.com/wwzzz/fedgs -https://github.com/deu30303/feddefender -https://github.com/bingzhaozhu/xtab -https://github.com/google-research/federated https://github.com/zhuangdizhu/FedGen -https://github.com/ycao5602/KAFAL -https://github.com/wnma3mz/FedLMD -https://github.com/ShahryarBQ/EF_HC -https://github.com/ZFancy/SFAT -https://github.com/Chain123/Meta-HAR -https://github.com/HUST-EIC-AI-LAB/UCADI -https://github.com/IdanAchituve/pFedGP -https://github.com/xu-jingyi/fedcorr -https://github.com/basiralab/Fed-CBT -https://github.com/primihub/primihub -https://github.com/flint-xf-fan/Byzantine-Federeated-RL +https://github.com/siquanhuang/Multi-metrics_against_backdoors_in_FL +https://github.com/FederatedAI/KubeFATE +https://github.com/FETS-AI/Front-End +https://github.com/CharlieMat/EdgeCDR +https://github.com/codymlewis/viceroy +https://github.com/guskarls/dfl-pens https://github.com/AntixK/FedDyn -https://github.com/shenzebang/CENTAUR-Privacy-Federated-Representation-Learning -https://github.com/jhcknzzm/Federated-Learning-Backdoor/ -https://github.com/rithram/flynn -https://github.com/FederatedAI/FATE -https://github.com/trucndt/ami -https://github.com/unc-optimization/FedDR -https://github.com/FangXiuwen/AugHFL -https://github.com/melodi-lab/divfl -https://github.com/facebookresearch/canife -https://github.com/mengcz13/KDD2021_CNFGNN -https://github.com/bl166/wirelessfl-pdgnet -https://github.com/yuetan031/fedstar -https://github.com/cynricfu/fedhgn -https://github.com/a514514772/ProgFed -https://github.com/MTC-ETH/Federated-Learning-source/blob/master/dashboard/README.md -https://github.com/lunanbit/FedUL -https://github.com/conditionWang/FCIL -https://github.com/Samuel-Maddock/federated-boosted-dp-trees -https://github.com/farzanfarnia/RobustFL -https://github.com/mlcommons/MedPerf -https://github.com/daiqing98/FedCIL -https://github.com/wizard1203/VHL -https://github.com/sparsefed/sparsefed +https://github.com/JiahuaDong/FISS +https://github.com/yflyl613/fedrec +https://github.com/JYWa/FedNova +https://github.com/hongliny/FCO-ICML21 +https://github.com/mccorby/PhotoLabeller +https://github.com/fio1982/FlexiFed +https://github.com/flint-xf-fan/Byzantine-Federeated-RL +https://github.com/jcwang123/fedlc https://github.com/Spinozaaa/Federated-Long-tailed-Learning -https://github.com/yxdyc/pfedgate +https://github.com/tsingz0/fedcp +https://github.com/microsoft/msrflute +https://github.com/ghafeleb/Private-NonConvex-Federated-Learning-Without-a-Trusted-Server +https://github.com/alibaba/FederatedScope/tree/fedsp/federatedscope/nlp/fedsp https://github.com/optimization-ai/icml2023_fedxl -https://github.com/FengHZ/KD3A -https://github.com/harliwu/fedagrac -https://github.com/jw9msjwjnpdrlfw/tsfl -https://github.com/Sungwon-Han/FEDCPA -https://github.com/dual-grp/fedu_fmtl -https://github.com/corentingiraud/federated-learning-secure-aggregation -https://github.com/omarfoq/communication-in-cross-silo-fl -https://github.com/LatticeX-Foundation/Rosetta/blob/master/doc/DEPLOYMENT.md -https://github.com/ebagdasa/backdoor_federated_learning -https://github.com/arodio/ca-fed -https://github.com/Rachelxuan11/FLAME -https://github.com/benggggggggg/fedgame -https://github.com/junyizhu-ai/confidence_aware_pfl -https://github.com/Hypervoyager/PFL -https://github.com/cuhksz-nlp/ASA-TM -https://github.com/pps-lab/rofl-project-code -https://github.com/dawenzi098/SFL-Structural-Federated-Learning -https://github.com/AnselCmy/FedE -https://github.com/cisco-open/flame -https://github.com/wnn2000/fednoro -https://github.com/xkLi-Allen/FedGTA -https://github.com/illidanlab/FOSTER -https://github.com/OpenMined/PyVertical -https://github.com/QibingLee/OpenHealth -https://github.com/jeremy313/FL-WBC +https://github.com/maxencenoble/Differential-Privacy-for-Heterogeneous-Federated-Learning +https://github.com/HUST-EIC-AI-LAB/UCADI +https://github.com/KarhouTam/FedRecon +https://github.com/cuis15/FCFL +https://github.com/HuskyW/FFPA +https://github.com/JianXu95/FedPAC +https://github.com/facebookresearch/dp_compression https://github.com/hxwujinze/federated-deep-knowledge-tracing -https://github.com/FederatedAI/FATE/tree/master/python/federatedml/ensemble/secureboost -https://github.com/SongjieXie/Fed-SC +https://github.com/mlcommons/MedPerf +https://github.com/ebagdasa/backdoors101 +https://github.com/jialinyi94/doubly-stochastic-federataed-bandit +https://github.com/YMJS-Irfan/DP-FedSAM +https://github.com/JackqqWang/pfedHR +https://github.com/TsingZ0/PFL-Non-IID +https://github.com/FumiyukiKato/FL-TEE https://github.com/ccchengff/FDL/tree/main/playground/celu_vfl +https://github.com/MarcioPorto/federated-phenotyping +https://github.com/ElvisShaoYumeng/BLADE-FL https://github.com/LTTM/FedSpace/blob/main/media/slides.pdf -https://github.com/venkatesh-saligrama/Personalized-Federated-Learning -https://github.com/wuch15/FedPerGNN -https://github.com/cyberthreat-datasets/ctdd-2021-os-syslogs -https://github.com/PretomRoy/Defense-against-grad-inversion-attacks -https://github.com/divyansh03/fedexp -https://github.com/yuetan031/fedproto -https://github.com/Chen-Junbao/SecureAggregation -https://github.com/alibaba/FederatedScope/tree/master/benchmark/FedHPOBench -https://github.com/LTTM/FedSpace -https://github.com/imguangyu/fedperfix -https://github.com/OpenMined/SyferText -https://github.com/MoonkeyBoy/Federated-Unlearning-via-Class-Discriminative-Pruning -https://github.com/Xtra-Computing/PrivML -https://github.com/FETS-AI/Front-End -https://github.com/KAI-YUE/rog -https://github.com/cuis15/learning-to-collaborate -https://github.com/flair-thu/creamfl -https://github.com/MTC-ETH/Federated-Learning-source -https://github.com/sfu-db/FedRain-and-Frog -https://github.com/ybdai7/chameleon-durable-backdoor -https://github.com/maxinge8698/FedID -https://github.com/kiddyboots216/CommEfficient -https://github.com/tsingz0/fedala -https://github.com/Soptq/iccv23-3sfc +https://github.com/MingruiLiu-ML-Lab/episode +https://github.com/hmgxr128/MIFA_code/ +https://github.com/alibaba/FederatedScope +https://github.com/taoqi98/PrivateKT +https://github.com/cugzj/KT-pFL +https://github.com/HewlettPackard/swarm-learning +https://github.com/FedML-AI/FedML +https://github.com/SMILELab-FL/FedVocab +https://github.com/rand2ai/fedboost +https://github.com/huerdong/FedVert-Experiments +https://github.com/zshuai8/FedGMM_ICML2023 +https://github.com/ZackZikaiXiao/FedGraB +https://github.com/dem123456789/HeteroFL-Computation-and-Communication-Efficient-Federated-Learning-for-Heterogeneous-Clients +https://github.com/LabeliaLabs/distributed-learning-contributivity +https://github.com/IdanAchituve/pFedGP +https://github.com/ramshi236/Accelerated-Federated-Learning-Over-MAC-in-Heterogeneous-Networks +https://github.com/bytedance/fedlearner +https://github.com/jackie840129/fedfr +https://github.com/LipingYi/QSFL +https://github.com/ellenxtan/ifedtree +https://github.com/J1nqianChen/FedKA +https://github.com/haozhaowang/DaFKD2023 +https://github.com/citychan/federated-dpms +https://github.com/lancopku/fedmnmt +https://github.com/846468230/FedACK +https://github.com/google-research/federated/tree/f4e26c1b9b47ac320e520a8b9943ea2c5324b8c2/large_cohort +https://github.com/yjw1029/ua-fedrec +https://github.com/Thinklab-SJTU/GAMF +https://github.com/WenkeHuang/FSMAFL https://github.com/gamarcad/samba-demo -https://github.com/liecn/PyramidFL +https://github.com/rlphilli/Collaborative-Incentives +https://github.com/ShahryarBQ/EF_HC +https://github.com/ycruan/FedSoft +https://github.com/yasar-rehman/fedvssl +https://github.com/akhilmathurs/orchestra +https://github.com/zfan20/PFGNNPlus +https://github.com/FL-HAR/Graph-Federated-Learning-for-CIoT-Devices.git +https://github.com/shangxinyi/CReFF-FL +https://github.com/Astuary/Flow https://github.com/zaixizhang/FLDetector -https://github.com/jianyizhang123/FLOP -https://github.com/kpdonahue/model_sharing_games -https://github.com/intel/openfl -https://github.com/google/fedjax -https://github.com/liqi16/martfl -https://github.com/albietz/ppsgd -https://github.com/vaseline555/superfed -https://github.com/WwZzz/easyFL -https://github.com/rong-dai/DisPFL -https://github.com/carbonati/fl-zoo -https://github.com/AI-secure/CRFL -https://github.com/lins-lab/fedbr -https://github.com/xmed-lab/rscfed -https://github.com/YamingGuo98/FedIIR -https://github.com/sungwon-han/fedx -https://github.com/inspire-group/ModelPoisoning -https://github.com/XDUJiaweiChen/Dap-FL -https://github.com/REIYANG/FedBCD -https://github.com/ghafeleb/Private-NonConvex-Federated-Learning-Without-a-Trusted-Server -https://github.com/MSU-MLSys-Lab/FedRolex -https://github.com/daizhongxiang/Differentially-Private-Federated-Bayesian-Optimization -https://github.com/Di-Chai/FedEval -https://github.com/TinfoilHat0/Defending-Against-Backdoors-with-Robust-Learning-Rate -https://github.com/med-air/FedBN -https://github.com/IBM/flexfl -https://github.com/fedego/fedego -https://github.com/mc-nya/FedNest -https://github.com/bokun-wang/moml -https://github.com/bibikar/feddst -https://github.com/BUAA-CST/iLRG -https://github.com/bytedance/fedlearner -https://github.com/garyzhang99/DM-PFL -https://github.com/med-air/HarmoFL -https://github.com/clreda/near-optimal-federated -https://github.com/eniac/flamingo -https://github.com/liuquande/FedDG-ELCFS -https://github.com/TL-System/plato/tree/main/examples/knot -https://github.com/daizhongxiang/Federated_Bayesian_Optimization -https://github.com/FedML-AI/SpreadGNN -https://github.com/siquanhuang/Multi-metrics_against_backdoors_in_FL -https://github.com/garyxcheng/personalized-federated-learning -https://github.com/Xtra-Computing/FedSim -https://github.com/haoyuzhao123/coreset-vfl-codes -https://github.com/LabeliaLabs/distributed-learning-contributivity -https://github.com/taokz/FedR -https://github.com/tj-kim/pFedDef_v1 -https://github.com/JYWa/FedNova -https://github.com/pasquini-dario/eludingsecureaggregation -https://github.com/hangxu0304/DeepReduce -https://github.com/llm-eff/FedPepTAO -https://github.com/Zoesgithub/FedReg -https://github.com/maiph123/verticalgnn -https://github.com/GOGODD/FL-EDGE-COMPUTING/releases/tag/federated_learning -https://github.com/SMILELab-FL/FedLab -https://github.com/HewlettPackard/swarm-learning/blob/master/docs/videos.md -https://github.com/yh-yao/FedRule -https://github.com/lgcollins/FedRep +https://github.com/xidongwu/D-AUPRC +https://github.com/xuchenhao001/AFL +https://github.com/SymbioticLab/FedScale +https://github.com/nusdbsystem/falcon +https://github.com/privacytrustlab/ml_privacy_meter +https://github.com/krishnap25/FL_partial_personalization +https://github.com/XinyiYS/Gradient-Driven-Rewards-to-Guarantee-Fairness-in-Collaborative-Machine-Learning +https://github.com/FederatedAI/FATE +https://github.com/owkin/sratta +https://github.com/zhyczy/Fed-CO2 +https://github.com/hasakiXie123/FedCMR +https://github.com/xaynetwork/xaynet +https://github.com/Xtra-Computing/SimFL +https://github.com/andytu28/fps_pre-training +https://github.com/JonasGeiping/breaching +https://github.com/AI-secure/DBA +https://github.com/FedML-AI/FedML/tree/master/fedml_experiments/distributed/fedgkt +https://github.com/xkLi-Allen/FedGTA +https://github.com/HKUST-KnowComp/FKGE +https://github.com/eth-sri/bayes-framework-leakage https://github.com/TalwalkarLab/leaf -https://github.com/rasmus-pagh/private-countsketch -https://github.com/Xtra-Computing/NIID-Bench -https://github.com/FRM-Sec/FRM -https://github.com/hyhmia/DisTrans +https://github.com/wingter562/SAFA +https://github.com/ielab/2022-SIGIR-noniid-foltr +https://github.com/PaddlePaddle/PaddleFL +https://github.com/zhuohangli/GGL +https://github.com/FuChong-cyber/label-inference-attacks +https://github.com/junyizhu-ai/confidence_aware_pfl +https://github.com/google-research/federated/tree/master/reconstruction +https://github.com/wuch15/FedPerGNN +https://github.com/garyxcheng/personalized-federated-learning +https://github.com/shengchaochen82/metepfl +https://github.com/JedMills/Faster-FL +https://github.com/ZFancy/SFAT +https://github.com/boxinz17/data-market-via-adaptive-sampling +https://github.com/fedego/fedego +https://github.com/deep1401/fedmoji +https://github.com/dawenzi098/SFL-Structural-Federated-Learning +https://github.com/WeiNingChen/pbm +https://github.com/wrh14/learning_to_invert +https://github.com/taoqi98/FedSampling +https://github.com/EasyFL-AI/EasyFL +https://github.com/kpdonahue/model_sharing_games +https://github.com/shams-sam/FedOptim +https://github.com/clu5/federated-conformal +https://github.com/QinbinLi/MOON +https://github.com/HarlinLee/multitask-fusion +https://github.com/ShenGroup/FMAB +https://github.com/exquisite1210/PT-FUCH_P +https://github.com/microsoft/FedDrift https://github.com/YonghaiGong/FedADMM -https://github.com/jedmills/fedgbo -https://github.com/FedML-AI/FedGraphNN -https://github.com/litian96/fair_flearn -https://github.com/Batool-Salehi/FL-based-Sector-Selection -https://github.com/KarhouTam/Per-FedAvg -https://github.com/MingruiLiu-ML-Lab/episode -https://github.com/AI-secure/FLBenchmark-toolkit -https://github.com/ml-postech/gradient-inversion-generative-image-prior -https://github.com/gaoliang13/FedDC -https://github.com/nhatminh/FEDL-INFOCOM -https://github.com/KarhouTam/FedRecon -https://github.com/illidanlab/SplitMix -https://github.com/zshuai8/FedGMM_ICML2023 -https://github.com/Oxfordblue7/FedLIT -https://github.com/rlphilli/Collaborative-Incentives +https://github.com/chunmeifeng/fedins +https://github.com/chuanting/fedda +https://github.com/Chen-Junbao/SecureAggregation +https://github.com/wuch15/FedAttack +https://github.com/MediaBrain-SJTU/FedGELA https://github.com/amitport/DRIVE-One-bit-Distributed-Mean-Estimation -https://github.com/dual-grp/DONE -https://github.com/citychan/federated-dpms -https://github.com/zj-jayzhang/Federated-Class-Continual-Learning -https://github.com/BHui97/PrivateFL -https://github.com/konstmish/rr_prox_fed -https://github.com/cuis15/FCFL -https://github.com/DeRafael/CAFE -https://github.com/kaiyuanmifen/FederatedNLP -https://github.com/SkellamMixtureMechanism/SMM +https://github.com/MoonkeyBoy/Federated-Unlearning-via-Class-Discriminative-Pruning +https://github.com/zlz0414/FedDAR +https://github.com/gkaissis/PriMIA +https://github.com/iQua/flsim +https://github.com/omarfoq/FedEM +https://github.com/Substra/substra +https://github.com/sungwon-han/fedx +https://github.com/wwzzz/fedgs +https://github.com/liqi16/martfl +https://github.com/ycao5602/KAFAL +https://github.com/LatticeX-Foundation/Rosetta/blob/master/doc/DEPLOYMENT.md +https://github.com/nlokeshiisc/SFedAvg-AAAI21 +https://github.com/farzanfarnia/RobustFL +https://github.com/MLOPTPSU/FedTorch +https://github.com/hongyouc/Fed-RoD +https://github.com/morningd/flexcfl +https://github.com/Koukyosyumei/AIJack https://github.com/TL-System/plato -https://github.com/minglllli/CBAFed -https://github.com/MarcioPorto/federated-phenotyping -https://github.com/DCALab-UNIPV/Turning-Privacy-preserving-Mechanisms-against-Federated-Learning -https://github.com/lancopku/fedmnmt -https://github.com/AllenBeau/pFedBayes -https://github.com/JedMills/Faster-FL -https://github.com/FedML-AI/FedML/tree/master/fedml_experiments/distributed/fedgkt -https://github.com/Soptq/Overlap-FedAvg -https://github.com/ljaiverson/pgfed +https://github.com/hgh0545/graph-fraudster +https://github.com/iwang05/FLuID +https://github.com/rithram/flynn +https://github.com/pengyang7881187/fedrl +https://github.com/Accenture/Labs-Federated-Learning +https://github.com/liuquande/FedDG-ELCFS +https://github.com/sabersalehk/MRE_C +https://github.com/appy1608/EMNLP2023-Multimodal-Complaint-Detection +https://github.com/MTC-ETH/Federated-Learning-source/blob/master/dashboard/README.md +https://github.com/JinheonBaek/FED-PUB +https://github.com/imguangyu/fedperfix +https://github.com/Di-Chai/FedEval +https://github.com/TsingZ0/GPFL +https://github.com/GwenLegate/GuidingLastLayerFLPretrain +https://github.com/OpenMined/PySyft +https://github.com/lins-lab/fedbr https://github.com/Chung-ju/VFedTrans -https://github.com/rand2ai/fedboost -https://github.com/Hanzhouu/FedBFPT -https://github.com/jinkyu032/FedMLB -https://github.com/haoyangliASTAPLE/3DFed +https://github.com/omarfoq/knn-per +https://github.com/Samuel-Maddock/federated-boosted-dp-trees https://github.com/Accenture/Labs-Federated-Learning/tree/asynchronous_FL -https://github.com/LipingYi/QSFL +https://github.com/venkatesh-saligrama/Personalized-Federated-Learning +https://github.com/conditionWang/FCIL +https://github.com/jd-9n/9nfl +https://github.com/lkyddd/gradma +https://github.com/vrt1shjwlkr/NDSS21-Model-Poisoning +https://github.com/illidanlab/FADE +https://github.com/zhangcx19/ijcai-23-pfedrec +https://github.com/EasyFL-AI/EasyFL/tree/master/applications/mas +https://github.com/Sungwon-Han/FEDCPA +https://github.com/maxinge8698/FedID +https://github.com/dongzizhu/FedDA +https://github.com/xj231/featureinference-vfl +https://github.com/xjiajiahao/federated-minimax +https://github.com/kxzxvbk/Fling +https://github.com/JedMills/MTFL-For-Personalised-DNNs +https://github.com/omarfoq/streaming-fl +https://github.com/cisco-open/flame +https://github.com/facebookresearch/FLSim +https://github.com/yh-yao/FedGCN +https://github.com/enosair/federated-fdp +https://github.com/LightSecAgg/MLSys2022_anonymous +https://github.com/baichuanzheng1/fedgat +https://github.com/harliwu/fedagrac +https://github.com/jichan3751/ifca +https://github.com/MediaBrain-SJTU/pFedGraph +https://github.com/bibikar/feddst +https://github.com/QibingLee/OpenHealth +https://github.com/usc-sail/fed-multimodal +https://github.com/Zoesgithub/FedReg +https://github.com/SAP-samples/machine-learning-diff-private-federated-learning +https://github.com/cyyever/distributed_learning_simulator +https://github.com/VITA-Group/MaT-FL +https://github.com/Yujun-Shi/FedCLS +https://github.com/google-research/federated/tree/master/optimization +https://github.com/CityU-AIM-Group/FedPD +https://github.com/gdisag/gradient_disaggregation +https://github.com/SonyAI/MocoSFL +https://github.com/yutong-dai/fednh +https://github.com/MehdiSet/PerFedMask +https://github.com/litian96/fair_flearn +https://github.com/wenkehuang/fccl +https://github.com/jhoon-oh/FedBABU +https://github.com/nlokeshiisc/sfedavg-aaai21 +https://github.com/ShenglongZhou/FedADMM +https://github.com/SamuelHorvath/VR_Byzantine +https://github.com/ml-postech/gradient-inversion-generative-image-prior https://github.com/git-disl/STDLens -https://github.com/MediaBrain-SJTU/FedDG-GA -https://github.com/wrh14/learning_to_invert -https://github.com/raymin0223/LoGo -https://github.com/NVIDIA/NVFlare/tree/dev/research/fed-ce -https://github.com/Koukyosyumei/AIJack -https://github.com/shenzebang/Federated-Learning-Pytorch -https://github.com/aioz-ai/MultigraphFL -https://github.com/IBM/probabilistic-federated-neural-matching -https://github.com/hmgxr128/MIFA_code/ -https://github.com/OpenMined/PySyft -https://github.com/South-hw/FedPara_ICLR22 +https://github.com/xqlin98/Fair-yet-Equal-CML +https://github.com/yh-yao/FedRule +https://github.com/FRM-Sec/FRM +https://github.com/mysteryresearcher/dasha +https://github.com/hanguo97/expectation-propagation +https://github.com/TL-System/plato/tree/main/examples/knot +https://github.com/Soptq/Overlap-FedAvg +https://github.com/SymbioticLab/Oort +https://github.com/morningD/FlexCFL +https://github.com/FengHZ/KD3A +https://github.com/NVIDIA/NVFlare/tree/main/research/one-shot-vfl +https://github.com/melodi-lab/divfl +https://github.com/guopengf/Auto-FedRL +https://github.com/eric-ai-lab/FedVLN +https://github.com/chaoyitud/LeadFL +https://github.com/pasquini-dario/eludingsecureaggregation +https://github.com/cfh19980612/FedGraph +https://github.com/FederatedAI/FedVision +https://github.com/QuanlingZhao/FedHD +https://github.com/tfzhou/fedfa +https://github.com/pps-lab/rofl-project-code +https://github.com/minglllli/CBAFed +https://github.com/MTC-ETH/Federated-Learning-source +https://github.com/ljb121002/fednar +https://github.com/clreda/near-optimal-federated +https://github.com/lgcollins/FedRep +https://github.com/guopengf/FL-MRCM +https://github.com/llm-eff/FedPepTAO +https://github.com/tj-kim/pFedDef_v1 +https://github.com/tensorflow/federated +https://github.com/IntelligentNetworkingLAB/Graph-Neural-Network-based-Federated-Learning-for-Heterogenous-Device-Network +https://github.com/lwz001/FML-ST +https://github.com/mkhodak/fedex +https://github.com/lxcnju/FedRepo +https://github.com/bl166/wirelessfl-pdgnet +https://github.com/Awesome-Image-Registration-Organization/awesome-image-registration +https://github.com/dual-grp/DONE +https://github.com/ybdai7/chameleon-durable-backdoor https://github.com/adap/flower -https://github.com/Princeton-SysML/FILM +https://github.com/scaleoutsystems/fedn +https://github.com/AI-secure/CRFL +https://github.com/jeremy313/Soteria +https://github.com/wudonglei99/smartidx +https://github.com/AvivSham/pFedHN https://github.com/git-disl/scale-fl -https://github.com/andytu28/fps_pre-training -https://github.com/JonasGeiping/invertinggradients -https://github.com/alibaba/FederatedScope/tree/fedsp/federatedscope/nlp/fedsp -https://github.com/tfzhou/fedfa -https://github.com/CharlieMat/EdgeCDR -https://github.com/guskarls/dfl-pens -https://github.com/alibaba-edu/mpc4j/tree/main/mpc4j-sml-opboost -https://github.com/purp1eHaze/FedIPR https://github.com/wenzhu23333/Differential-Privacy-Based-Federated-Learning -https://github.com/yjw1029/ua-fedrec -https://github.com/ShenglongZhou/FedADMM -https://github.com/wyjeong/FedMatch -https://github.com/zhangcx19/ijcai-23-pfedrec -https://github.com/zkhku/fedsage -https://github.com/microsoft/msrflute -https://github.com/xidongwu/D-AUPRC -https://github.com/tensorflow/federated -https://github.com/google-research/federated/tree/f4e26c1b9b47ac320e520a8b9943ea2c5324b8c2/large_cohort -https://github.com/lx10077/fedavgpy -https://github.com/deep1401/fedmoji -https://github.com/JedMills/MTFL-For-Personalised-DNNs -https://github.com/cfh19980612/FedGraph -https://github.com/kxzxvbk/Fling -https://github.com/YangLiangwei/FeSoG -https://github.com/jichan3751/ifca -https://github.com/tsingz0/fedcp -https://github.com/lkyddd/gradma -https://github.com/dongzizhu/FedDA -https://github.com/CodePothunter/fednp -https://github.com/shangxinyi/CReFF-FL -https://github.com/FedML-AI/FedNLP -https://github.com/Oxfordblue7/GCFL -https://github.com/morningd/flexcfl -https://github.com/jialinyi94/doubly-stochastic-federataed-bandit -https://github.com/XinyiYS/Gradient-Driven-Rewards-to-Guarantee-Fairness-in-Collaborative-Machine-Learning -https://github.com/cap-ntu/FedReID -https://github.com/846468230/FedACK -https://github.com/innovation-cat/Awesome-Federated-Machine-Learning +https://github.com/LiruichenSpace/FedFusion +https://github.com/TsingZ0/PFLlib +https://github.com/mengcz13/KDD2021_CNFGNN +https://github.com/primihub/primihub +https://github.com/zjukg/maker +https://github.com/PKU-Chengxu/FLASH +https://github.com/google-research/federated/tree/master/private_linear_compression +https://github.com/AnselCmy/FedE +https://github.com/DeRafael/CAFE +https://github.com/med-air/HarmoFL +https://github.com/lzcemma/RACE_Distance +https://github.com/Kira0096/PBPFL +https://github.com/luozhengquan/DFL +https://github.com/daizhongxiang/Differentially-Private-Federated-Bayesian-Optimization +https://github.com/SongjieXie/Fed-SC +https://github.com/sfu-db/FedRain-and-Frog +https://github.com/totilas/padadmm +https://github.com/yjw1029/Efficient-FedRec +https://github.com/cyberthreat-datasets/ctdd-2021-os-syslogs +https://github.com/lebyni/PFA +https://github.com/basiralab/reproducibleFedGNN https://github.com/international-explore/awesome-privacy-chinese -https://github.com/vrt1shjwlkr/NDSS21-Model-Poisoning -https://github.com/yasar-rehman/fedvssl -https://github.com/FederatedAI/FedVision -https://github.com/google-research/federated/tree/master/gans +https://github.com/culiver/SPACE +https://github.com/Liangqiong/ViT-FL-main +https://github.com/cynricfu/FedHGN +https://github.com/haozzh/FedCR https://github.com/matenure/federated_feature_fusion -https://github.com/AI-secure/DBA +https://github.com/DCALab-UNIPV/Turning-Privacy-preserving-Mechanisms-against-Federated-Learning +https://github.com/shenzebang/CENTAUR-Privacy-Federated-Representation-Learning +https://github.com/jinkyu032/FedMLB +https://github.com/XunKaiLi/Awesome-GNN-Research +https://github.com/eniac/flamingo +https://github.com/Oxfordblue7/GCFL https://github.com/imkevinkuo/noisy-eval-in-fl -https://github.com/raipranav/fcl-fedseit -https://github.com/weimingwill/awesome-federated-learning -https://github.com/CharlieDinh/pFedMe +https://github.com/RamiHaf/Explainable-Federated-Learning-via-Random-Forests +https://github.com/GalaxyLearning/GFL +https://github.com/inspire-group/ModelPoisoning +https://github.com/abhimanyudubey/private_federated_linear_bandits +https://github.com/morningD/GrouProx https://github.com/zexilee/iccv-2023-fedetf -https://github.com/exquisite1210/PT-FUCH_P -https://github.com/SMILELab-FL/FedVocab -https://github.com/basiralab/reproducibleFedGNN -https://github.com/AmberLJC/FLsystem-paper -https://github.com/xuchenhao001/AFL -https://github.com/Raymw/Federated-XGBoost -https://github.com/TL-System/plato/ -https://github.com/privacytrustlab/ml_privacy_meter -https://github.com/Kira0096/PBPFL +https://github.com/YuchenLiu-a/byzantine-gas +https://github.com/varnio/fedsim +https://github.com/ZJU-DIVER/ShapleyFL-Robust-Federated-Learning-Based-on-Shapley-Value +https://github.com/hfzhang31/A3FL +https://github.com/FederalLab/OpenFed/ +https://github.com/google-research/dataset_grouper +https://github.com/czhang024/CI-Net +https://github.com/giemp95/feddti +https://github.com/gaoliang13/FedDC +https://github.com/liboyue/beer +https://github.com/hongliny/FedAc-NeurIPS20 +https://github.com/llpilla/energy-optimal-federated-learning +https://github.com/MSU-MLSys-Lab/FedRolex +https://github.com/hit-mdc/FedTSC-FedST https://github.com/mmorafah/pacfl +https://github.com/peterhan91/Thorax_GAN +https://github.com/Batool-Salehi/FL-based-Sector-Selection +https://github.com/cynricfu/fedhgn +https://github.com/FedML-AI/SpreadGNN +https://github.com/viktorvaladi/fedval +https://github.com/FedML-AI/FedCV +https://github.com/jw9msjwjnpdrlfw/tsfl +https://github.com/mindspore-ai/mindspore/tree/master/docs/api/api_python/federated +https://github.com/jma78/FedGTF-EF +https://github.com/andylamp/federated_pca +https://github.com/illidanlab/FOSTER +https://github.com/alibaba/Elastic-Federated-Learning-Solution/tree/FedAds +https://github.com/taokz/FedR +https://github.com/zeyu-zh/TrustFL +https://github.com/alibaba/FederatedScope/tree/backdoor-bench +https://github.com/cap-ntu/FedReID +https://github.com/huweibo/Awesome-Federated-Learning-on-Graph-and-GNN-papers +https://github.com/Oxfordblue7/FedLIT +https://github.com/ShenGroup/PF_MAB +https://github.com/owkin/FLamby https://github.com/junyizhu-ai/surrogate_model_extension -https://github.com/Thinklab-SJTU/GAMF -https://github.com/lingjuanlv/FPPDL -https://github.com/pengyang7881187/fedrl -https://github.com/google-research/federated/tree/master/reconstruction -https://github.com/FederatedAI/KubeFATE -https://github.com/songw-sw/f2l -https://github.com/FangXiuwen/Robust_FL -https://github.com/jd-9n/9nfl -https://github.com/facebookresearch/where_to_begin -https://github.com/yjw1029/Efficient-FedRec -https://github.com/cyyever/distributed_learning_simulator -https://github.com/omarfoq/FedEM -https://github.com/maxencenoble/Differential-Privacy-for-Heterogeneous-Federated-Learning -https://github.com/CodePothunter/fednp/blob/main/appendix.pdf -https://github.com/google-research/federated/tree/master/distributed_dp -https://github.com/guopengf/FL-MRCM -https://github.com/ljaiverson/pFL-APPLE +https://github.com/zhenqincn/FedAPEN +https://github.com/QinbinLi/FedKT +https://github.com/benggggggggg/fedgame +https://github.com/wyjeong/FedWeIT +https://github.com/raipranav/fcl-fedseit +https://github.com/TsingZ0/DBE +https://github.com/XDUJiaweiChen/Dap-FL +https://github.com/fedlearnAI/fedlearn-algo +https://github.com/wnn2000/fednoro +https://github.com/daiqing98/FedCIL +https://github.com/nhatminh/FEDL-INFOCOM +https://github.com/FederatedAI/FATE-Serving +https://github.com/weimingwill/awesome-federated-learning +https://github.com/raymin0223/LoGo +https://github.com/GanyuWang/VFL-CZOFO +https://github.com/git-disl/Lockdown +https://github.com/WwZzz/easyFL https://github.com/google-research/federated/tree/7525c36324cb022bc05c3fce88ef01147cae9740/periodic_distribution_shift -https://github.com/cyrilli/Async-LinUCB -https://github.com/lowya/private-federated-learning-without-a-trusted-server -https://github.com/chandra2thapa/SplitFed-When-Federated-Learning-Meets-Split-Learning -https://github.com/yzhao062/anomaly-detection-resources +https://github.com/Strange369/TypedDAG_on_HeteroMP +https://github.com/YamingGuo98/FedIIR +https://github.com/KarhouTam/Per-FedAvg +https://github.com/songw-sw/f2l +https://github.com/LatticeX-Foundation/Rosetta +https://github.com/lokinko/Federated-Learning +https://github.com/AmberLJC/FLsystem-paper +https://github.com/liehe/byzantine-robust-noniid-optimizer +https://github.com/IBM/probabilistic-federated-neural-matching +https://github.com/LipingYi/FedGH +https://github.com/zkhku/fedsage +https://github.com/IBM/federated-learning-lib/blob/main/docs/papers.md +https://github.com/trucndt/ami +https://github.com/orionw/multilingual-federated-learning https://github.com/secretflow/secretflow +https://github.com/google-research/federated/tree/master/gans +https://github.com/PretomRoy/Defense-against-grad-inversion-attacks https://github.com/zlijingtao/ResSFL -https://github.com/J1nqianChen/FedKA +https://github.com/mtang724/Self-Balancing-Federated-Learning +https://github.com/BHui97/PrivateFL +https://github.com/carbonati/fl-zoo +https://github.com/cuhksz-nlp/ASA-TM +https://github.com/HewlettPackard/swarm-learning/blob/master/docs/videos.md +https://github.com/sarapieri/fed_het +https://github.com/SEED-VT/FedDebug +https://github.com/alshedivat/fedpa +https://github.com/Koukyosyumei/NAIST-FedML-Experiments +https://github.com/visitworld123/fedfed +https://github.com/jedmills/fedgbo +https://github.com/shenzebang/Federated-Learning-Pytorch +https://github.com/AI-secure/FedGame +https://github.com/lingjuanlv/FPPDL +https://github.com/balanced-fl/Addressing-Class-Imbalance-FL +https://github.com/mc-nya/FedNest +https://github.com/debcaldarola/fedsam +https://github.com/rdz98/fedrecattack +https://github.com/nusdbsystem/pivot +https://github.com/konstmish/rr_prox_fed https://github.com/litian96/ditto -https://github.com/haozhaowang/DaFKD2023 +https://github.com/MediaBrain-SJTU/FedDisco +https://github.com/Hanzhouu/FedBFPT +https://github.com/cyrilli/Async-LinUCB +https://github.com/kiddyboots216/CommEfficient +https://github.com/IBM/flexfl +https://github.com/ljaiverson/pFL-APPLE +https://github.com/lunanbit/FedUL +https://github.com/HikariX/MP-FedXGB +https://github.com/CharlieDinh/pFedMe +https://github.com/jianyizhang123/FLOP +https://github.com/FederatedAI/FATE/tree/master/python/federatedml/ensemble/secureboost +https://github.com/google-research/federated/tree/master/generalization +https://github.com/TL-System/plato/ +https://github.com/FederalLab/OpenFed +https://github.com/yxdyc/pfedgate +https://github.com/BUAA-CST/iLRG +https://github.com/bokun-wang/moml +https://github.com/HaifengXia/PSE +https://github.com/illidanlab/SplitMix +https://github.com/Xtra-Computing/NIID-Bench https://github.com/littlesunlxy/fedpu-torch -https://github.com/XunKaiLi/Awesome-GNN-Research -https://github.com/hongliny/FCO-ICML21 -https://github.com/baowenxuan/fedcollab +https://github.com/AffectFAL/AffectFAL +https://github.com/xiyuanyang45/DynamicPFL https://github.com/ahmedcs/refl -https://github.com/dunchen/AsyncDrop__Release -https://github.com/Princeton-SysML/GradAttack -https://github.com/jcwang123/fedlc -https://github.com/nusdbsystem/pivot -https://github.com/dem123456789/HeteroFL-Computation-and-Communication-Efficient-Federated-Learning-for-Heterogeneous-Clients -https://github.com/SymbioticLab/Oort -https://github.com/gkaissis/PriMIA -https://github.com/WenkeHuang/RethinkFL -https://github.com/SMILELab-FL/FedLab-benchmarks -https://github.com/lokinko/Federated-Learning -https://github.com/zlz0414/FedDAR -https://github.com/Emory-AIMS/PFA -https://github.com/Awesome-Image-Registration-Organization/awesome-image-registration -https://github.com/HikariX/MP-FedXGB -https://github.com/gcfgae/GCFGAE -https://github.com/yh-yao/FedGCN -https://github.com/TsingZ0/PFLlib -https://github.com/HewlettPackard/swarm-learning -https://github.com/MediaBrain-SJTU/pFedGraph -https://github.com/GalaxyLearning/GFL -https://github.com/jackie840129/fedfr -https://github.com/EasyFL-AI/EasyFL/tree/master/applications/mas +https://github.com/yuxuanzhang0713/fedcsr +https://github.com/haoyangliASTAPLE/3DFed +https://github.com/Kthyeon/ssfod +https://github.com/sail-research/iba +https://github.com/liecn/PyramidFL +https://github.com/Chain123/Meta-HAR +https://github.com/jhcknzzm/Federated-Learning-Backdoor/ +https://github.com/vaseline555/superfed +https://github.com/google-research/federated +https://github.com/IBM/federated-learning-lib +https://github.com/wanglun1996/secure-robust-federated-learning +https://github.com/lowya/private-federated-learning-without-a-trusted-server +https://github.com/Raymw/Federated-XGBoost +https://github.com/FangXiuwen/AugHFL +https://github.com/layer6ai-labs/ProxyFL +https://github.com/flair-thu/creamfl +https://github.com/chandra2thapa/SplitFed-When-Federated-Learning-Meets-Split-Learning +https://github.com/Princeton-SysML/FILM +https://github.com/litian96/FedProx +https://github.com/REIYANG/FedBCD +https://github.com/xidongwu/Federated-Minimax-and-Conditional-Stochastic-Optimization/tree/main +https://github.com/aioz-ai/MultigraphFL https://github.com/nju-websoft/FedLU -https://github.com/amitport/EDEN-Distributed-Mean-Estimation -https://github.com/taoqi98/FedSampling -https://github.com/Koukyosyumei/NAIST-FedML-Experiments -https://github.com/hongliny/FedAc-NeurIPS20 -https://github.com/owkin/FLamby -https://github.com/osu-nlp-group/fl4semanticparsing -https://github.com/LatticeX-Foundation/Rosetta -https://github.com/boxinz17/data-market-via-adaptive-sampling -https://github.com/ShenGroup/FMAB -https://github.com/zjukg/maker -https://github.com/mccorby/PhotoLabeller -https://github.com/chaoyanghe/Awesome-Federated-Learning -https://github.com/usc-sail/fed-multimodal -https://github.com/YMJS-Irfan/DP-FedSAM -https://github.com/FederatedAI/research -https://github.com/saist1993/dpnlp -https://github.com/AfoninAndrei/ICLR2022 -https://github.com/EasyFL-AI/EasyFL -https://github.com/yutong-dai/fednh +https://github.com/AllenBeau/pFedBayes +https://github.com/AI-secure/FLBenchmark-toolkit +https://github.com/youngfish42/FL-paper-update-tracker +https://github.com/a514514772/ProgFed +https://github.com/TinfoilHat0/Defending-Against-Backdoors-with-Robust-Learning-Rate +https://github.com/SMILELab-FL/FedLab-benchmarks +https://github.com/baowenxuan/ATP +https://github.com/zexilee/icml-2023-fedlaw +https://github.com/alibaba/FederatedScope/tree/FSreal +https://github.com/Xtra-Computing/PrivML https://github.com/chunmeifeng/FedPR -https://github.com/cynricfu/FedHGN -https://github.com/mtang724/Self-Balancing-Federated-Learning -https://github.com/CGCL-codes/pFedSD -https://github.com/SamuelHorvath/VR_Byzantine -https://github.com/SymbioticLab/FedScale -https://github.com/codymlewis/viceroy -https://github.com/NVIDIA/NVFlare +https://github.com/alibaba/FederatedScope/tree/master/benchmark/FedHPOBench +https://github.com/sunjunaimer/TPAMI-LAQ +https://github.com/DianboWork/FedDS +https://github.com/Rachelxuan11/FLAME +https://github.com/baowenxuan/fedcollab +https://github.com/cuis15/learning-to-collaborate +https://github.com/zj-jayzhang/Federated-Class-Continual-Learning +https://github.com/SMILELab-FL/FedLab +https://github.com/MediaBrain-SJTU/FedDG-GA +https://github.com/rasmus-pagh/private-countsketch +https://github.com/daizhongxiang/Federated_Bayesian_Optimization +https://github.com/intel/openfl +https://github.com/South-hw/FedPara_ICLR22 +https://github.com/royson/fedl2p/ +https://github.com/liyipeng00/convergence +https://github.com/facebookresearch/canife +https://github.com/GOGODD/FL-EDGE-COMPUTING/releases/tag/federated_learning +https://github.com/zhaohaoru/federated-clustering-of-bandits +https://github.com/NVlabs/FedFomo +https://github.com/FangXiuwen/Robust_FL +https://github.com/wizard1203/VHL +https://github.com/divyansh03/fedexp +https://github.com/yuetan031/fedproto +https://github.com/hongyouc/fedbe +https://github.com/hongliny/sharp-bounds-for-fedavg-and-continuous-perspective +https://github.com/MingruiLiu-ML-Lab/episode_plusplus +https://github.com/wnma3mz/FedLMD +https://github.com/arodio/ca-fed +https://github.com/albietz/ppsgd +https://github.com/amitport/EDEN-Distributed-Mean-Estimation +https://github.com/qizhuang-qz/FedCSPC https://github.com/anishacharya/DeLiCoCo -https://github.com/jma78/FedGTF-EF -https://github.com/ZJU-DIVER/ShapleyFL-Robust-Federated-Learning-Based-on-Shapley-Value -https://github.com/hgh0545/graph-fraudster -https://github.com/czhang024/CI-Net -https://github.com/teijyogen/secsv -https://github.com/MingruiLiu-ML-Lab/Federated-Sparse-Learning -https://github.com/SEED-VT/FedDebug -https://github.com/MehdiSet/PerFedMask -https://github.com/QinbinLi/FedKT -https://github.com/morningD/GrouProx +https://github.com/osu-nlp-group/fl4semanticparsing +https://github.com/kaiyuanmifen/FederatedNLP +https://github.com/dual-grp/fedu_fmtl +https://github.com/Distributed-Learning-Networking-Group/FedMoS/ +https://github.com/JonasGeiping/invertinggradients https://github.com/FederatedAI/research/tree/main/publications/FedCG -https://github.com/hongyouc/Fed-RoD -https://github.com/krishnap25/FL_partial_personalization -https://github.com/YuchenLiu-a/byzantine-gas +https://github.com/LTTM/FedSpace +https://github.com/deu30303/feddefender +https://github.com/shahakash28/simc +https://github.com/alibaba-edu/mpc4j/tree/main/mpc4j-sml-opboost +https://github.com/FedML-AI/FedGraphNN +https://github.com/innovation-cat/Awesome-Federated-Machine-Learning +https://github.com/KAI-YUE/rog +https://github.com/corentingiraud/federated-learning-secure-aggregation https://github.com/IBM/FedMA -https://github.com/HaifengXia/PSE -https://github.com/totilas/padadmm -https://github.com/gdisag/gradient_disaggregation -https://github.com/xaynetwork/xaynet -https://github.com/hanguo97/expectation-propagation -https://github.com/alshedivat/fedpa -https://github.com/TsingZ0/GPFL -https://github.com/wanglun1996/secure-robust-federated-learning -https://github.com/harliwu/fedamd -https://github.com/andylamp/federated_pca +https://github.com/yuetan031/fedstar +https://github.com/Hypervoyager/PFL +https://github.com/facebookresearch/where_to_begin +https://github.com/rong-dai/DisPFL +https://github.com/xidongwu/Federated-Minimax-and-Conditional-Stochastic-Optimization/ +https://github.com/omarfoq/communication-in-cross-silo-fl +https://github.com/OpenMined/PyVertical +https://github.com/ml-unito/federation_boosting +https://github.com/NVIDIA/NVFlare +https://github.com/jeremy313/FL-WBC +https://github.com/ebagdasa/backdoor_federated_learning +https://github.com/med-air/FedBN +https://github.com/SaraBabakN/MFCL-NeurIPS23 +https://github.com/ljaiverson/pgfed +https://github.com/pierreHmbt/FedCP-QQ +https://github.com/CGCL-codes/pFedSD +https://github.com/aelgabli/FedNew +https://github.com/SkellamMixtureMechanism/SMM +https://github.com/hyhmia/DisTrans +https://github.com/Ruiquan5514/Federated-Linear-Contextual-Bandits +https://github.com/saist1993/dpnlp +https://github.com/OpenMined/SyferText +https://github.com/Emory-AIMS/PFA +https://github.com/xmed-lab/rscfed +https://github.com/KaiyuanZh/FLIP +https://github.com/garyzhang99/DM-PFL +https://github.com/nds2022/SGBoost +https://github.com/AfoninAndrei/ICLR2022 +https://github.com/mmendiet/FedAlign +https://github.com/xu-jingyi/fedcorr https://github.com/KAI-YUE/ntk-fed -https://github.com/xjiajiahao/federated-minimax -https://github.com/debcaldarola/fedsam +https://github.com/FedML-AI/FedNLP https://github.com/gingsmith/fmtl -https://github.com/fio1982/FlexiFed -https://github.com/TsingZ0/PFL-Non-IID -https://github.com/xj231/featureinference-vfl -https://github.com/IntelligentNetworkingLAB/Graph-Neural-Network-based-Federated-Learning-for-Heterogenous-Device-Network -https://github.com/jinghuichen/focused-flip-federated-backdoor-attack -https://github.com/jhoon-oh/FedBABU -https://github.com/huweibo/Awesome-Federated-Learning-on-Graph-and-GNN-papers -https://github.com/QinbinLi/MOON -https://github.com/PaddlePaddle/PaddleFL -https://github.com/nds2022/SGBoost -https://github.com/eric-ai-lab/FedVLN -https://github.com/guopengf/Auto-FedRL -https://github.com/shams-sam/FedOptim -https://github.com/lwz001/FML-ST -https://github.com/hongyouc/fedbe -https://github.com/wingter562/SAFA -https://github.com/wuch15/FedAttack -https://github.com/microsoft/FedDrift -https://github.com/zhuohangli/GGL -https://github.com/LipingYi/FedGH -https://github.com/ml-unito/federation_boosting -https://github.com/eth-sri/bayes-framework-leakage -https://github.com/liboyue/beer -https://github.com/baichuanzheng1/fedgat -https://github.com/owkin/sratta -https://github.com/sabersalehk/MRE_C -https://github.com/ielab/2022-SIGIR-noniid-foltr -https://github.com/Yujun-Shi/FedCLS -https://github.com/orionw/multilingual-federated-learning -https://github.com/youngfish42/FL-paper-update-tracker -https://github.com/taoqi98/PrivateKT -https://github.com/Distributed-Learning-Networking-Group/FedMoS/ -https://github.com/layer6ai-labs/ProxyFL -https://github.com/WenkeHuang/FSMAFL -https://github.com/zhenqincn/FedAPEN -https://github.com/JonasGeiping/breaching -https://github.com/ycruan/FedSoft -https://github.com/hasakiXie123/FedCMR -https://github.com/NVIDIA/NVFlare/tree/main/research/one-shot-vfl -https://github.com/viktorvaladi/fedval -https://github.com/jeremy313/Soteria -https://github.com/youngfish42/Awesome-FL/issues -https://github.com/Strange369/TypedDAG_on_HeteroMP -https://github.com/wenkehuang/fccl -https://github.com/HKUST-KnowComp/FKGE -https://github.com/enosair/federated-fdp -https://github.com/liehe/byzantine-robust-noniid-optimizer -https://github.com/PKU-Chengxu/FLASH -https://github.com/AffectFAL/AffectFAL -https://github.com/JinheonBaek/FED-PUB -https://github.com/google-research/federated/tree/master/private_linear_compression -https://github.com/zexilee/icml-2023-fedlaw -https://github.com/mysteryresearcher/dasha -https://github.com/mindspore-ai/mindspore/tree/master/docs/api/api_python/federated -https://github.com/cugzj/KT-pFL -https://github.com/akhilmathurs/orchestra -https://github.com/zhanghangtao/poisoning-attack-on-fl -https://github.com/zhaohaoru/federated-clustering-of-bandits -https://github.com/wudonglei99/smartidx -https://github.com/jiayunz/fedalign -https://github.com/wyjeong/FedWeIT -https://github.com/chunmeifeng/fedins +https://github.com/bingzhaozhu/xtab https://github.com/TCtower/GlueFL -https://github.com/ebagdasa/backdoors101 -https://github.com/qizhuang-qz/FedCSPC +https://github.com/haoyuzhao123/coreset-vfl-codes https://github.com/ignavierng/notears-admm -https://github.com/chuanting/fedda -https://github.com/yuxuanzhang0713/fedcsr -https://github.com/FederalLab/OpenFed/ -https://github.com/FumiyukiKato/FL-TEE -https://github.com/mkhodak/fedex -https://github.com/fedlearnAI/fedlearn-algo -https://github.com/FedML-AI/FedML -https://github.com/shengchaochen82/metepfl 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-https://github.com/IBM/federated-learning-lib/blob/main/docs/papers.md -https://github.com/litian96/FedProx -https://github.com/facebookresearch/FLSim -https://github.com/epfml/federated-learning-public-code/tree/master/codes/FedDF-code -https://github.com/shahakash28/simc -https://github.com/appy1608/EMNLP2023-Multimodal-Complaint-Detection -https://github.com/llpilla/energy-optimal-federated-learning -https://github.com/HarlinLee/multitask-fusion -https://github.com/APPFL/APPFL -https://github.com/LightSecAgg/MLSys2022_anonymous -https://github.com/SAP-samples/machine-learning-diff-private-federated-learning -https://github.com/haozzh/FedCR -https://github.com/alibaba/FederatedScope -https://github.com/MLOPTPSU/FedTorch -https://github.com/chaoyitud/LeadFL -https://github.com/alibaba/Elastic-Federated-Learning-Solution/tree/FedAds -https://github.com/Liangqiong/ViT-FL-main -https://github.com/huerdong/FedVert-Experiments -https://github.com/peterhan91/Thorax_GAN -https://github.com/clu5/federated-conformal -https://github.com/google-research/federated/tree/master/generalization -https://github.com/ellenxtan/ifedtree -https://github.com/nlokeshiisc/SFedAvg-AAAI21 -https://github.com/Ruiquan5514/Federated-Linear-Contextual-Bandits +https://github.com/Xtra-Computing/FedSim +https://github.com/chaoyanghe/Awesome-Federated-Learning +https://github.com/gcfgae/GCFGAE +https://github.com/jiayunz/fedalign diff --git a/go.mod b/go.mod index 0a6c4f5..2854296 100644 --- a/go.mod +++ b/go.mod @@ -3,556 +3,586 @@ https://github.com/youngfish42/Awesome-FL go 1.16 require ( - https://github.com/JianXu95/FedPAC v0.0.0 - https://github.com/abhimanyudubey/private_federated_linear_bandits v0.0.0 - https://github.com/google-research/federated/tree/master/optimization v0.0.0 - https://github.com/NVlabs/FedFomo v0.0.0 - https://github.com/cuhksz-nlp/GCASeg v0.0.0 - https://github.com/giemp95/feddti v0.0.0 - https://github.com/omarfoq/streaming-fl v0.0.0 - https://github.com/ramshi236/Accelerated-Federated-Learning-Over-MAC-in-Heterogeneous-Networks v0.0.0 - https://github.com/aelgabli/FedNew v0.0.0 - https://github.com/alibaba/FederatedScope/tree/backdoor-bench v0.0.0 - https://github.com/hit-mdc/FedTSC-FedST v0.0.0 - https://github.com/morningD/FlexCFL v0.0.0 - https://github.com/RamiHaf/Explainable-Federated-Learning-via-Random-Forests v0.0.0 - https://github.com/luozhengquan/DFL v0.0.0 - https://github.com/ElvisShaoYumeng/BLADE-FL v0.0.0 - https://github.com/KaiyuanZh/FLIP v0.0.0 - https://github.com/JiahuaDong/FISS v0.0.0 - https://github.com/mmendiet/FedAlign v0.0.0 - https://github.com/facebookresearch/dp_compression v0.0.0 - https://github.com/FederalLab/OpenFed v0.0.0 - https://github.com/MediaBrain-SJTU/FedDisco v0.0.0 - https://github.com/omarfoq/knn-per v0.0.0 - https://github.com/eth-sri/tableak v0.0.0 - https://github.com/Xtra-Computing/FedTree v0.0.0 - https://github.com/sunjunaimer/TPAMI-LAQ v0.0.0 - https://github.com/alibaba/FederatedScope/tree/FSreal v0.0.0 - https://github.com/xqlin98/Fair-yet-Equal-CML v0.0.0 - https://github.com/VITA-Group/MaT-FL v0.0.0 - https://github.com/illidanlab/FADE v0.0.0 - https://github.com/DianboWork/FedDS v0.0.0 - https://github.com/varnio/fedsim v0.0.0 - https://github.com/zfan20/PFGNNPlus v0.0.0 - https://github.com/rdz98/fedrecattack v0.0.0 - https://github.com/Accenture/Labs-Federated-Learning v0.0.0 - https://github.com/LiruichenSpace/FedFusion v0.0.0 - https://github.com/nusdbsystem/falcon v0.0.0 - https://github.com/hongliny/sharp-bounds-for-fedavg-and-continuous-perspective v0.0.0 - https://github.com/WeiNingChen/pbm v0.0.0 - https://github.com/FuChong-cyber/label-inference-attacks v0.0.0 - https://github.com/wwzzz/fedgs v0.0.0 - https://github.com/deu30303/feddefender v0.0.0 - https://github.com/bingzhaozhu/xtab v0.0.0 - https://github.com/google-research/federated v0.0.0 - https://github.com/zhuangdizhu/FedGen v0.0.0 - https://github.com/ycao5602/KAFAL v0.0.0 - https://github.com/wnma3mz/FedLMD v0.0.0 - https://github.com/ShahryarBQ/EF_HC v0.0.0 - https://github.com/ZFancy/SFAT v0.0.0 - https://github.com/Chain123/Meta-HAR v0.0.0 - https://github.com/HUST-EIC-AI-LAB/UCADI v0.0.0 - https://github.com/IdanAchituve/pFedGP v0.0.0 - https://github.com/xu-jingyi/fedcorr v0.0.0 - https://github.com/basiralab/Fed-CBT v0.0.0 - https://github.com/primihub/primihub v0.0.0 - https://github.com/flint-xf-fan/Byzantine-Federeated-RL v0.0.0 - https://github.com/AntixK/FedDyn v0.0.0 - https://github.com/shenzebang/CENTAUR-Privacy-Federated-Representation-Learning v0.0.0 - https://github.com/jhcknzzm/Federated-Learning-Backdoor/ v0.0.0 - https://github.com/rithram/flynn v0.0.0 - https://github.com/FederatedAI/FATE v0.0.0 - https://github.com/trucndt/ami v0.0.0 - https://github.com/unc-optimization/FedDR v0.0.0 - https://github.com/FangXiuwen/AugHFL v0.0.0 - https://github.com/melodi-lab/divfl v0.0.0 - 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- https://github.com/layer6ai-labs/ProxyFL v0.0.0 - https://github.com/WenkeHuang/FSMAFL v0.0.0 - https://github.com/zhenqincn/FedAPEN v0.0.0 - https://github.com/JonasGeiping/breaching v0.0.0 - https://github.com/ycruan/FedSoft v0.0.0 - https://github.com/hasakiXie123/FedCMR v0.0.0 - https://github.com/NVIDIA/NVFlare/tree/main/research/one-shot-vfl v0.0.0 - https://github.com/viktorvaladi/fedval v0.0.0 - https://github.com/jeremy313/Soteria v0.0.0 - https://github.com/youngfish42/Awesome-FL/issues v0.0.0 - https://github.com/Strange369/TypedDAG_on_HeteroMP v0.0.0 - https://github.com/wenkehuang/fccl v0.0.0 - https://github.com/HKUST-KnowComp/FKGE v0.0.0 - https://github.com/enosair/federated-fdp v0.0.0 - https://github.com/liehe/byzantine-robust-noniid-optimizer v0.0.0 - https://github.com/PKU-Chengxu/FLASH v0.0.0 - https://github.com/AffectFAL/AffectFAL v0.0.0 - https://github.com/JinheonBaek/FED-PUB v0.0.0 - https://github.com/google-research/federated/tree/master/private_linear_compression v0.0.0 - https://github.com/zexilee/icml-2023-fedlaw v0.0.0 - https://github.com/mysteryresearcher/dasha v0.0.0 - https://github.com/mindspore-ai/mindspore/tree/master/docs/api/api_python/federated v0.0.0 - https://github.com/cugzj/KT-pFL v0.0.0 - https://github.com/akhilmathurs/orchestra v0.0.0 - https://github.com/zhanghangtao/poisoning-attack-on-fl v0.0.0 - https://github.com/zhaohaoru/federated-clustering-of-bandits v0.0.0 - https://github.com/wudonglei99/smartidx v0.0.0 - https://github.com/jiayunz/fedalign v0.0.0 - https://github.com/wyjeong/FedWeIT v0.0.0 - https://github.com/chunmeifeng/fedins v0.0.0 - https://github.com/TCtower/GlueFL v0.0.0 - https://github.com/ebagdasa/backdoors101 v0.0.0 - https://github.com/qizhuang-qz/FedCSPC v0.0.0 - https://github.com/ignavierng/notears-admm v0.0.0 - https://github.com/chuanting/fedda v0.0.0 - https://github.com/yuxuanzhang0713/fedcsr v0.0.0 - https://github.com/FederalLab/OpenFed/ v0.0.0 - https://github.com/FumiyukiKato/FL-TEE v0.0.0 - https://github.com/mkhodak/fedex v0.0.0 - https://github.com/fedlearnAI/fedlearn-algo v0.0.0 - https://github.com/FedML-AI/FedML v0.0.0 - https://github.com/shengchaochen82/metepfl v0.0.0 - https://github.com/zeyu-zh/TrustFL v0.0.0 - https://github.com/FL-HAR/Graph-Federated-Learning-for-CIoT-Devices.git v0.0.0 - https://github.com/lxcnju/FedRepo v0.0.0 - https://github.com/yflyl613/fedrec v0.0.0 - https://github.com/pierreHmbt/FedCP-QQ v0.0.0 - https://github.com/SMILELab-FL/FedLegal v0.0.0 - https://github.com/CityU-AIM-Group/FedPD v0.0.0 - https://github.com/FedML-AI/FedCV v0.0.0 - https://github.com/Substra/substra v0.0.0 - https://github.com/balanced-fl/Addressing-Class-Imbalance-FL v0.0.0 - https://github.com/SonyAI/MocoSFL v0.0.0 - https://github.com/nlokeshiisc/sfedavg-aaai21 v0.0.0 - https://github.com/scaleoutsystems/fedn v0.0.0 - https://github.com/Xtra-Computing/SimFL v0.0.0 - https://github.com/FederatedAI/FATE-Serving v0.0.0 - https://github.com/IBM/federated-learning-lib v0.0.0 - https://github.com/HuskyW/FFPA v0.0.0 - https://github.com/lebyni/PFA v0.0.0 - https://github.com/iQua/flsim v0.0.0 - https://github.com/AvivSham/pFedHN v0.0.0 - https://github.com/ShenGroup/PF_MAB v0.0.0 - https://github.com/QuanlingZhao/FedHD v0.0.0 - https://github.com/IBM/federated-learning-lib/blob/main/docs/papers.md v0.0.0 - https://github.com/litian96/FedProx v0.0.0 - https://github.com/facebookresearch/FLSim v0.0.0 - https://github.com/epfml/federated-learning-public-code/tree/master/codes/FedDF-code v0.0.0 - https://github.com/shahakash28/simc v0.0.0 - https://github.com/appy1608/EMNLP2023-Multimodal-Complaint-Detection v0.0.0 - https://github.com/llpilla/energy-optimal-federated-learning v0.0.0 - https://github.com/HarlinLee/multitask-fusion v0.0.0 - https://github.com/APPFL/APPFL v0.0.0 - https://github.com/LightSecAgg/MLSys2022_anonymous v0.0.0 - https://github.com/SAP-samples/machine-learning-diff-private-federated-learning v0.0.0 - https://github.com/haozzh/FedCR v0.0.0 - https://github.com/alibaba/FederatedScope v0.0.0 - https://github.com/MLOPTPSU/FedTorch v0.0.0 - https://github.com/chaoyitud/LeadFL v0.0.0 - https://github.com/alibaba/Elastic-Federated-Learning-Solution/tree/FedAds v0.0.0 - https://github.com/Liangqiong/ViT-FL-main v0.0.0 - https://github.com/huerdong/FedVert-Experiments v0.0.0 - https://github.com/peterhan91/Thorax_GAN v0.0.0 - https://github.com/clu5/federated-conformal v0.0.0 - https://github.com/google-research/federated/tree/master/generalization v0.0.0 - https://github.com/ellenxtan/ifedtree v0.0.0 - https://github.com/nlokeshiisc/SFedAvg-AAAI21 v0.0.0 - https://github.com/Ruiquan5514/Federated-Linear-Contextual-Bandits v0.0.0 + github.com/maiph123/verticalgnn v0.0.0 // indirect + github.com/insujeon/MetaVD v0.0.0 // indirect + github.com/sparsefed/sparsefed v0.0.0 // indirect + github.com/cuhksz-nlp/GCASeg v0.0.0 // indirect + github.com/basiralab/Fed-CBT v0.0.0 // indirect + github.com/unc-optimization/FedDR v0.0.0 // indirect + github.com/eth-sri/tableak v0.0.0 // indirect + github.com/jinghuichen/focused-flip-federated-backdoor-attack v0.0.0 // indirect + github.com/Princeton-SysML/GradAttack v0.0.0 // indirect + github.com/google/fedjax v0.0.0 // indirect + github.com/NVIDIA/NVFlare/tree/dev/research/fed-ce v0.0.0 // indirect + github.com/dunchen/AsyncDrop__Release v0.0.0 // indirect + github.com/CodePothunter/fednp v0.0.0 // indirect + github.com/CodePothunter/fednp/blob/main/appendix.pdf v0.0.0 // indirect + github.com/wyjeong/FedMatch v0.0.0 // indirect + github.com/harliwu/fedamd v0.0.0 // indirect + github.com/APPFL/APPFL v0.0.0 // indirect + github.com/MingruiLiu-ML-Lab/Federated-Sparse-Learning v0.0.0 // indirect + github.com/teijyogen/secsv v0.0.0 // indirect + github.com/purp1eHaze/FedIPR v0.0.0 // indirect + github.com/hangxu0304/DeepReduce v0.0.0 // indirect + github.com/YangLiangwei/FeSoG v0.0.0 // indirect + github.com/bdemo/pfedbred_public v0.0.0 // indirect + github.com/epfml/federated-learning-public-code/tree/master/codes/FedDF-code v0.0.0 // indirect + github.com/google-research/federated/tree/master/distributed_dp v0.0.0 // indirect + github.com/FederatedAI/research v0.0.0 // indirect + github.com/yzhao062/anomaly-detection-resources v0.0.0 // indirect + github.com/Soptq/iccv23-3sfc v0.0.0 // indirect + github.com/zhanghangtao/poisoning-attack-on-fl v0.0.0 // indirect + github.com/WenkeHuang/RethinkFL v0.0.0 // indirect + github.com/tsingz0/fedala v0.0.0 // indirect + github.com/lx10077/fedavgpy v0.0.0 // indirect + github.com/Xtra-Computing/FedTree v0.0.0 // indirect + github.com/zhuangdizhu/FedGen v0.0.0 // indirect + github.com/siquanhuang/Multi-metrics_against_backdoors_in_FL v0.0.0 // indirect + github.com/FederatedAI/KubeFATE v0.0.0 // indirect + github.com/FETS-AI/Front-End v0.0.0 // indirect + github.com/CharlieMat/EdgeCDR v0.0.0 // indirect + github.com/codymlewis/viceroy v0.0.0 // indirect + github.com/guskarls/dfl-pens v0.0.0 // indirect + github.com/AntixK/FedDyn v0.0.0 // indirect + github.com/JiahuaDong/FISS v0.0.0 // indirect + github.com/yflyl613/fedrec v0.0.0 // indirect + github.com/JYWa/FedNova v0.0.0 // indirect + github.com/hongliny/FCO-ICML21 v0.0.0 // indirect + github.com/mccorby/PhotoLabeller v0.0.0 // indirect + github.com/fio1982/FlexiFed v0.0.0 // indirect + github.com/flint-xf-fan/Byzantine-Federeated-RL v0.0.0 // indirect + github.com/jcwang123/fedlc v0.0.0 // indirect + github.com/Spinozaaa/Federated-Long-tailed-Learning v0.0.0 // indirect + github.com/tsingz0/fedcp v0.0.0 // indirect + github.com/microsoft/msrflute v0.0.0 // indirect + github.com/ghafeleb/Private-NonConvex-Federated-Learning-Without-a-Trusted-Server v0.0.0 // indirect + github.com/alibaba/FederatedScope/tree/fedsp/federatedscope/nlp/fedsp v0.0.0 // indirect + github.com/optimization-ai/icml2023_fedxl v0.0.0 // indirect + github.com/maxencenoble/Differential-Privacy-for-Heterogeneous-Federated-Learning v0.0.0 // indirect + github.com/HUST-EIC-AI-LAB/UCADI v0.0.0 // indirect + github.com/KarhouTam/FedRecon v0.0.0 // indirect + github.com/cuis15/FCFL v0.0.0 // indirect + github.com/HuskyW/FFPA v0.0.0 // indirect + github.com/JianXu95/FedPAC v0.0.0 // indirect + github.com/facebookresearch/dp_compression v0.0.0 // indirect + github.com/hxwujinze/federated-deep-knowledge-tracing v0.0.0 // indirect + github.com/mlcommons/MedPerf v0.0.0 // indirect + github.com/ebagdasa/backdoors101 v0.0.0 // indirect + github.com/jialinyi94/doubly-stochastic-federataed-bandit v0.0.0 // indirect + github.com/YMJS-Irfan/DP-FedSAM v0.0.0 // indirect + github.com/JackqqWang/pfedHR v0.0.0 // indirect + github.com/TsingZ0/PFL-Non-IID v0.0.0 // indirect + github.com/FumiyukiKato/FL-TEE v0.0.0 // indirect + github.com/ccchengff/FDL/tree/main/playground/celu_vfl v0.0.0 // indirect + github.com/MarcioPorto/federated-phenotyping v0.0.0 // indirect + github.com/ElvisShaoYumeng/BLADE-FL v0.0.0 // indirect + github.com/LTTM/FedSpace/blob/main/media/slides.pdf v0.0.0 // indirect + github.com/MingruiLiu-ML-Lab/episode v0.0.0 // indirect + github.com/hmgxr128/MIFA_code/ v0.0.0 // indirect + github.com/alibaba/FederatedScope v0.0.0 // indirect + github.com/taoqi98/PrivateKT v0.0.0 // indirect + github.com/cugzj/KT-pFL v0.0.0 // indirect + github.com/HewlettPackard/swarm-learning v0.0.0 // indirect + github.com/FedML-AI/FedML v0.0.0 // indirect + github.com/SMILELab-FL/FedVocab v0.0.0 // indirect + github.com/rand2ai/fedboost v0.0.0 // indirect + github.com/huerdong/FedVert-Experiments v0.0.0 // indirect + github.com/zshuai8/FedGMM_ICML2023 v0.0.0 // indirect + github.com/ZackZikaiXiao/FedGraB v0.0.0 // indirect + github.com/dem123456789/HeteroFL-Computation-and-Communication-Efficient-Federated-Learning-for-Heterogeneous-Clients v0.0.0 // indirect + github.com/LabeliaLabs/distributed-learning-contributivity v0.0.0 // indirect + github.com/IdanAchituve/pFedGP v0.0.0 // indirect + github.com/ramshi236/Accelerated-Federated-Learning-Over-MAC-in-Heterogeneous-Networks v0.0.0 // indirect + github.com/bytedance/fedlearner v0.0.0 // indirect + github.com/jackie840129/fedfr v0.0.0 // indirect + github.com/LipingYi/QSFL v0.0.0 // indirect + github.com/ellenxtan/ifedtree v0.0.0 // indirect + github.com/J1nqianChen/FedKA v0.0.0 // indirect + github.com/haozhaowang/DaFKD2023 v0.0.0 // indirect + github.com/citychan/federated-dpms v0.0.0 // indirect + github.com/lancopku/fedmnmt v0.0.0 // indirect + github.com/846468230/FedACK v0.0.0 // indirect + github.com/google-research/federated/tree/f4e26c1b9b47ac320e520a8b9943ea2c5324b8c2/large_cohort v0.0.0 // indirect + github.com/yjw1029/ua-fedrec v0.0.0 // indirect + github.com/Thinklab-SJTU/GAMF v0.0.0 // indirect + github.com/WenkeHuang/FSMAFL v0.0.0 // indirect + github.com/gamarcad/samba-demo v0.0.0 // indirect + github.com/rlphilli/Collaborative-Incentives v0.0.0 // indirect + github.com/ShahryarBQ/EF_HC v0.0.0 // indirect + github.com/ycruan/FedSoft v0.0.0 // indirect + github.com/yasar-rehman/fedvssl v0.0.0 // indirect + github.com/akhilmathurs/orchestra v0.0.0 // indirect + github.com/zfan20/PFGNNPlus v0.0.0 // indirect + github.com/FL-HAR/Graph-Federated-Learning-for-CIoT-Devices.git v0.0.0 // indirect + github.com/shangxinyi/CReFF-FL v0.0.0 // indirect + github.com/Astuary/Flow v0.0.0 // indirect + github.com/zaixizhang/FLDetector v0.0.0 // indirect + github.com/xidongwu/D-AUPRC v0.0.0 // indirect + github.com/xuchenhao001/AFL v0.0.0 // indirect + github.com/SymbioticLab/FedScale v0.0.0 // indirect + github.com/nusdbsystem/falcon v0.0.0 // indirect + github.com/privacytrustlab/ml_privacy_meter v0.0.0 // indirect + github.com/krishnap25/FL_partial_personalization v0.0.0 // indirect + github.com/XinyiYS/Gradient-Driven-Rewards-to-Guarantee-Fairness-in-Collaborative-Machine-Learning v0.0.0 // indirect + github.com/FederatedAI/FATE v0.0.0 // indirect + github.com/owkin/sratta v0.0.0 // indirect + github.com/zhyczy/Fed-CO2 v0.0.0 // indirect + github.com/hasakiXie123/FedCMR v0.0.0 // indirect + github.com/xaynetwork/xaynet v0.0.0 // indirect + github.com/Xtra-Computing/SimFL v0.0.0 // indirect + github.com/andytu28/fps_pre-training v0.0.0 // indirect + github.com/JonasGeiping/breaching v0.0.0 // indirect + github.com/AI-secure/DBA v0.0.0 // indirect + github.com/FedML-AI/FedML/tree/master/fedml_experiments/distributed/fedgkt v0.0.0 // indirect + github.com/xkLi-Allen/FedGTA v0.0.0 // indirect + github.com/HKUST-KnowComp/FKGE v0.0.0 // indirect + github.com/eth-sri/bayes-framework-leakage v0.0.0 // indirect + github.com/TalwalkarLab/leaf v0.0.0 // indirect + github.com/wingter562/SAFA v0.0.0 // indirect + github.com/ielab/2022-SIGIR-noniid-foltr v0.0.0 // indirect + github.com/PaddlePaddle/PaddleFL v0.0.0 // indirect + github.com/zhuohangli/GGL v0.0.0 // indirect + github.com/FuChong-cyber/label-inference-attacks v0.0.0 // indirect + github.com/junyizhu-ai/confidence_aware_pfl v0.0.0 // indirect + github.com/google-research/federated/tree/master/reconstruction v0.0.0 // indirect + github.com/wuch15/FedPerGNN v0.0.0 // indirect + github.com/garyxcheng/personalized-federated-learning v0.0.0 // indirect + github.com/shengchaochen82/metepfl v0.0.0 // indirect + github.com/JedMills/Faster-FL v0.0.0 // indirect + github.com/ZFancy/SFAT v0.0.0 // indirect + github.com/boxinz17/data-market-via-adaptive-sampling v0.0.0 // indirect + github.com/fedego/fedego v0.0.0 // indirect + github.com/deep1401/fedmoji v0.0.0 // indirect + github.com/dawenzi098/SFL-Structural-Federated-Learning v0.0.0 // indirect + github.com/WeiNingChen/pbm v0.0.0 // indirect + github.com/wrh14/learning_to_invert v0.0.0 // indirect + github.com/taoqi98/FedSampling v0.0.0 // indirect + github.com/EasyFL-AI/EasyFL v0.0.0 // indirect + github.com/kpdonahue/model_sharing_games v0.0.0 // indirect + github.com/shams-sam/FedOptim v0.0.0 // indirect + github.com/clu5/federated-conformal v0.0.0 // indirect + github.com/QinbinLi/MOON v0.0.0 // indirect + github.com/HarlinLee/multitask-fusion v0.0.0 // indirect + github.com/ShenGroup/FMAB v0.0.0 // indirect + github.com/exquisite1210/PT-FUCH_P v0.0.0 // indirect + github.com/microsoft/FedDrift v0.0.0 // indirect + github.com/YonghaiGong/FedADMM v0.0.0 // indirect + github.com/chunmeifeng/fedins v0.0.0 // indirect + github.com/chuanting/fedda v0.0.0 // indirect + github.com/Chen-Junbao/SecureAggregation v0.0.0 // indirect + github.com/wuch15/FedAttack v0.0.0 // indirect + github.com/MediaBrain-SJTU/FedGELA v0.0.0 // indirect + github.com/amitport/DRIVE-One-bit-Distributed-Mean-Estimation v0.0.0 // indirect + github.com/MoonkeyBoy/Federated-Unlearning-via-Class-Discriminative-Pruning v0.0.0 // indirect + github.com/zlz0414/FedDAR v0.0.0 // indirect + github.com/gkaissis/PriMIA v0.0.0 // indirect + github.com/iQua/flsim v0.0.0 // indirect + github.com/omarfoq/FedEM v0.0.0 // indirect + github.com/Substra/substra v0.0.0 // indirect + github.com/sungwon-han/fedx v0.0.0 // indirect + github.com/wwzzz/fedgs v0.0.0 // indirect + github.com/liqi16/martfl v0.0.0 // indirect + github.com/ycao5602/KAFAL v0.0.0 // indirect + github.com/LatticeX-Foundation/Rosetta/blob/master/doc/DEPLOYMENT.md v0.0.0 // indirect + github.com/nlokeshiisc/SFedAvg-AAAI21 v0.0.0 // indirect + github.com/farzanfarnia/RobustFL v0.0.0 // indirect + github.com/MLOPTPSU/FedTorch v0.0.0 // indirect + github.com/hongyouc/Fed-RoD v0.0.0 // indirect + github.com/morningd/flexcfl v0.0.0 // indirect + github.com/Koukyosyumei/AIJack v0.0.0 // indirect + github.com/TL-System/plato v0.0.0 // indirect + github.com/hgh0545/graph-fraudster v0.0.0 // indirect + github.com/iwang05/FLuID v0.0.0 // indirect + github.com/rithram/flynn v0.0.0 // indirect + github.com/pengyang7881187/fedrl v0.0.0 // indirect + github.com/Accenture/Labs-Federated-Learning v0.0.0 // indirect + github.com/liuquande/FedDG-ELCFS v0.0.0 // indirect + github.com/sabersalehk/MRE_C v0.0.0 // indirect + github.com/appy1608/EMNLP2023-Multimodal-Complaint-Detection v0.0.0 // indirect + github.com/MTC-ETH/Federated-Learning-source/blob/master/dashboard/README.md v0.0.0 // indirect + github.com/JinheonBaek/FED-PUB v0.0.0 // indirect + github.com/imguangyu/fedperfix v0.0.0 // indirect + github.com/Di-Chai/FedEval v0.0.0 // indirect + github.com/TsingZ0/GPFL v0.0.0 // indirect + github.com/GwenLegate/GuidingLastLayerFLPretrain v0.0.0 // indirect + github.com/OpenMined/PySyft v0.0.0 // indirect + github.com/lins-lab/fedbr v0.0.0 // indirect + github.com/Chung-ju/VFedTrans v0.0.0 // indirect + github.com/omarfoq/knn-per v0.0.0 // indirect + github.com/Samuel-Maddock/federated-boosted-dp-trees v0.0.0 // indirect + github.com/Accenture/Labs-Federated-Learning/tree/asynchronous_FL v0.0.0 // indirect + github.com/venkatesh-saligrama/Personalized-Federated-Learning v0.0.0 // indirect + github.com/conditionWang/FCIL v0.0.0 // indirect + github.com/jd-9n/9nfl v0.0.0 // indirect + github.com/lkyddd/gradma v0.0.0 // indirect + github.com/vrt1shjwlkr/NDSS21-Model-Poisoning v0.0.0 // indirect + github.com/illidanlab/FADE v0.0.0 // indirect + github.com/zhangcx19/ijcai-23-pfedrec v0.0.0 // indirect + github.com/EasyFL-AI/EasyFL/tree/master/applications/mas v0.0.0 // indirect + github.com/Sungwon-Han/FEDCPA v0.0.0 // indirect + github.com/maxinge8698/FedID v0.0.0 // indirect + github.com/dongzizhu/FedDA v0.0.0 // indirect + github.com/xj231/featureinference-vfl v0.0.0 // indirect + github.com/xjiajiahao/federated-minimax v0.0.0 // indirect + github.com/kxzxvbk/Fling v0.0.0 // indirect + github.com/JedMills/MTFL-For-Personalised-DNNs v0.0.0 // indirect + github.com/omarfoq/streaming-fl v0.0.0 // indirect + github.com/cisco-open/flame v0.0.0 // indirect + github.com/facebookresearch/FLSim v0.0.0 // indirect + github.com/yh-yao/FedGCN v0.0.0 // indirect + github.com/enosair/federated-fdp v0.0.0 // indirect + github.com/LightSecAgg/MLSys2022_anonymous v0.0.0 // indirect + github.com/baichuanzheng1/fedgat v0.0.0 // indirect + github.com/harliwu/fedagrac v0.0.0 // indirect + github.com/jichan3751/ifca v0.0.0 // indirect + github.com/MediaBrain-SJTU/pFedGraph v0.0.0 // indirect + github.com/bibikar/feddst v0.0.0 // indirect + github.com/QibingLee/OpenHealth v0.0.0 // indirect + github.com/usc-sail/fed-multimodal v0.0.0 // indirect + github.com/Zoesgithub/FedReg v0.0.0 // indirect + github.com/SAP-samples/machine-learning-diff-private-federated-learning v0.0.0 // indirect + github.com/cyyever/distributed_learning_simulator v0.0.0 // indirect + github.com/VITA-Group/MaT-FL v0.0.0 // indirect + github.com/Yujun-Shi/FedCLS v0.0.0 // indirect + github.com/google-research/federated/tree/master/optimization v0.0.0 // indirect + github.com/CityU-AIM-Group/FedPD v0.0.0 // indirect + github.com/gdisag/gradient_disaggregation v0.0.0 // indirect + github.com/SonyAI/MocoSFL v0.0.0 // indirect + github.com/yutong-dai/fednh v0.0.0 // indirect + github.com/MehdiSet/PerFedMask v0.0.0 // indirect + github.com/litian96/fair_flearn v0.0.0 // indirect + github.com/wenkehuang/fccl v0.0.0 // indirect + github.com/jhoon-oh/FedBABU v0.0.0 // indirect + github.com/nlokeshiisc/sfedavg-aaai21 v0.0.0 // indirect + github.com/ShenglongZhou/FedADMM v0.0.0 // indirect + github.com/SamuelHorvath/VR_Byzantine v0.0.0 // indirect + github.com/ml-postech/gradient-inversion-generative-image-prior v0.0.0 // indirect + github.com/git-disl/STDLens v0.0.0 // indirect + github.com/xqlin98/Fair-yet-Equal-CML v0.0.0 // indirect + github.com/yh-yao/FedRule v0.0.0 // indirect + github.com/FRM-Sec/FRM v0.0.0 // indirect + github.com/mysteryresearcher/dasha v0.0.0 // indirect + github.com/hanguo97/expectation-propagation v0.0.0 // indirect + github.com/TL-System/plato/tree/main/examples/knot v0.0.0 // indirect + github.com/Soptq/Overlap-FedAvg v0.0.0 // indirect + github.com/SymbioticLab/Oort v0.0.0 // indirect + github.com/morningD/FlexCFL v0.0.0 // indirect + github.com/FengHZ/KD3A v0.0.0 // indirect + github.com/NVIDIA/NVFlare/tree/main/research/one-shot-vfl v0.0.0 // indirect + github.com/melodi-lab/divfl v0.0.0 // indirect + github.com/guopengf/Auto-FedRL v0.0.0 // indirect + github.com/eric-ai-lab/FedVLN v0.0.0 // indirect + github.com/chaoyitud/LeadFL v0.0.0 // indirect + github.com/pasquini-dario/eludingsecureaggregation v0.0.0 // indirect + github.com/cfh19980612/FedGraph v0.0.0 // indirect + github.com/FederatedAI/FedVision v0.0.0 // indirect + github.com/QuanlingZhao/FedHD v0.0.0 // indirect + github.com/tfzhou/fedfa v0.0.0 // indirect + github.com/pps-lab/rofl-project-code v0.0.0 // indirect + github.com/minglllli/CBAFed v0.0.0 // indirect + github.com/MTC-ETH/Federated-Learning-source v0.0.0 // indirect + github.com/ljb121002/fednar v0.0.0 // indirect + github.com/clreda/near-optimal-federated v0.0.0 // indirect + github.com/lgcollins/FedRep v0.0.0 // indirect + github.com/guopengf/FL-MRCM v0.0.0 // indirect + github.com/llm-eff/FedPepTAO v0.0.0 // indirect + github.com/tj-kim/pFedDef_v1 v0.0.0 // indirect + github.com/tensorflow/federated v0.0.0 // indirect + github.com/IntelligentNetworkingLAB/Graph-Neural-Network-based-Federated-Learning-for-Heterogenous-Device-Network v0.0.0 // indirect + github.com/lwz001/FML-ST v0.0.0 // indirect + github.com/mkhodak/fedex v0.0.0 // indirect + github.com/lxcnju/FedRepo v0.0.0 // indirect + github.com/bl166/wirelessfl-pdgnet v0.0.0 // indirect + github.com/Awesome-Image-Registration-Organization/awesome-image-registration v0.0.0 // indirect + github.com/dual-grp/DONE v0.0.0 // indirect + github.com/ybdai7/chameleon-durable-backdoor v0.0.0 // indirect + github.com/adap/flower v0.0.0 // indirect + github.com/scaleoutsystems/fedn v0.0.0 // indirect + github.com/AI-secure/CRFL v0.0.0 // indirect + github.com/jeremy313/Soteria v0.0.0 // indirect + github.com/wudonglei99/smartidx v0.0.0 // indirect + github.com/AvivSham/pFedHN v0.0.0 // indirect + github.com/git-disl/scale-fl v0.0.0 // indirect + github.com/wenzhu23333/Differential-Privacy-Based-Federated-Learning v0.0.0 // indirect + github.com/LiruichenSpace/FedFusion v0.0.0 // indirect + github.com/TsingZ0/PFLlib v0.0.0 // indirect + github.com/mengcz13/KDD2021_CNFGNN v0.0.0 // indirect + github.com/primihub/primihub v0.0.0 // indirect + github.com/zjukg/maker v0.0.0 // indirect + github.com/PKU-Chengxu/FLASH v0.0.0 // indirect + github.com/google-research/federated/tree/master/private_linear_compression v0.0.0 // indirect + github.com/AnselCmy/FedE v0.0.0 // indirect + github.com/DeRafael/CAFE v0.0.0 // indirect + github.com/med-air/HarmoFL v0.0.0 // indirect + github.com/lzcemma/RACE_Distance v0.0.0 // indirect + github.com/Kira0096/PBPFL v0.0.0 // indirect + github.com/luozhengquan/DFL v0.0.0 // indirect + github.com/daizhongxiang/Differentially-Private-Federated-Bayesian-Optimization v0.0.0 // indirect + github.com/SongjieXie/Fed-SC v0.0.0 // indirect + github.com/sfu-db/FedRain-and-Frog v0.0.0 // indirect + github.com/totilas/padadmm v0.0.0 // indirect + github.com/yjw1029/Efficient-FedRec v0.0.0 // indirect + github.com/cyberthreat-datasets/ctdd-2021-os-syslogs v0.0.0 // indirect + github.com/lebyni/PFA v0.0.0 // indirect + github.com/basiralab/reproducibleFedGNN v0.0.0 // indirect + github.com/international-explore/awesome-privacy-chinese v0.0.0 // indirect + github.com/culiver/SPACE v0.0.0 // indirect + github.com/Liangqiong/ViT-FL-main v0.0.0 // indirect + github.com/cynricfu/FedHGN v0.0.0 // indirect + github.com/haozzh/FedCR v0.0.0 // indirect + github.com/matenure/federated_feature_fusion v0.0.0 // indirect + github.com/DCALab-UNIPV/Turning-Privacy-preserving-Mechanisms-against-Federated-Learning v0.0.0 // indirect + github.com/shenzebang/CENTAUR-Privacy-Federated-Representation-Learning v0.0.0 // indirect + github.com/jinkyu032/FedMLB v0.0.0 // indirect + github.com/XunKaiLi/Awesome-GNN-Research v0.0.0 // indirect + github.com/eniac/flamingo v0.0.0 // indirect + github.com/Oxfordblue7/GCFL v0.0.0 // indirect + github.com/imkevinkuo/noisy-eval-in-fl v0.0.0 // indirect + github.com/RamiHaf/Explainable-Federated-Learning-via-Random-Forests v0.0.0 // indirect + github.com/GalaxyLearning/GFL v0.0.0 // indirect + github.com/inspire-group/ModelPoisoning v0.0.0 // indirect + github.com/abhimanyudubey/private_federated_linear_bandits v0.0.0 // indirect + github.com/morningD/GrouProx v0.0.0 // indirect + github.com/zexilee/iccv-2023-fedetf v0.0.0 // indirect + github.com/YuchenLiu-a/byzantine-gas v0.0.0 // indirect + github.com/varnio/fedsim v0.0.0 // indirect + github.com/ZJU-DIVER/ShapleyFL-Robust-Federated-Learning-Based-on-Shapley-Value v0.0.0 // indirect + github.com/hfzhang31/A3FL v0.0.0 // indirect + github.com/FederalLab/OpenFed/ v0.0.0 // indirect + github.com/google-research/dataset_grouper v0.0.0 // indirect + github.com/czhang024/CI-Net v0.0.0 // indirect + github.com/giemp95/feddti v0.0.0 // indirect + github.com/gaoliang13/FedDC v0.0.0 // indirect + github.com/liboyue/beer v0.0.0 // indirect + github.com/hongliny/FedAc-NeurIPS20 v0.0.0 // indirect + github.com/llpilla/energy-optimal-federated-learning v0.0.0 // indirect + github.com/MSU-MLSys-Lab/FedRolex v0.0.0 // indirect + github.com/hit-mdc/FedTSC-FedST v0.0.0 // indirect + github.com/mmorafah/pacfl v0.0.0 // indirect + github.com/peterhan91/Thorax_GAN v0.0.0 // indirect + github.com/Batool-Salehi/FL-based-Sector-Selection v0.0.0 // indirect + github.com/cynricfu/fedhgn v0.0.0 // indirect + github.com/FedML-AI/SpreadGNN v0.0.0 // indirect + github.com/viktorvaladi/fedval v0.0.0 // indirect + github.com/FedML-AI/FedCV v0.0.0 // indirect + github.com/jw9msjwjnpdrlfw/tsfl v0.0.0 // indirect + github.com/mindspore-ai/mindspore/tree/master/docs/api/api_python/federated v0.0.0 // indirect + github.com/jma78/FedGTF-EF v0.0.0 // indirect + github.com/andylamp/federated_pca v0.0.0 // indirect + github.com/illidanlab/FOSTER v0.0.0 // indirect + github.com/alibaba/Elastic-Federated-Learning-Solution/tree/FedAds v0.0.0 // indirect + github.com/taokz/FedR v0.0.0 // indirect + github.com/zeyu-zh/TrustFL v0.0.0 // indirect + github.com/alibaba/FederatedScope/tree/backdoor-bench v0.0.0 // indirect + github.com/cap-ntu/FedReID v0.0.0 // indirect + github.com/huweibo/Awesome-Federated-Learning-on-Graph-and-GNN-papers v0.0.0 // indirect + github.com/Oxfordblue7/FedLIT v0.0.0 // indirect + github.com/ShenGroup/PF_MAB v0.0.0 // indirect + github.com/owkin/FLamby v0.0.0 // indirect + github.com/junyizhu-ai/surrogate_model_extension v0.0.0 // indirect + github.com/zhenqincn/FedAPEN v0.0.0 // indirect + github.com/QinbinLi/FedKT v0.0.0 // indirect + github.com/benggggggggg/fedgame v0.0.0 // indirect + github.com/wyjeong/FedWeIT v0.0.0 // indirect + github.com/raipranav/fcl-fedseit v0.0.0 // indirect + github.com/TsingZ0/DBE v0.0.0 // indirect + github.com/XDUJiaweiChen/Dap-FL v0.0.0 // indirect + github.com/fedlearnAI/fedlearn-algo v0.0.0 // indirect + github.com/wnn2000/fednoro v0.0.0 // indirect + github.com/daiqing98/FedCIL v0.0.0 // indirect + github.com/nhatminh/FEDL-INFOCOM v0.0.0 // indirect + github.com/FederatedAI/FATE-Serving v0.0.0 // indirect + github.com/weimingwill/awesome-federated-learning v0.0.0 // indirect + github.com/raymin0223/LoGo v0.0.0 // indirect + github.com/GanyuWang/VFL-CZOFO v0.0.0 // indirect + github.com/git-disl/Lockdown v0.0.0 // indirect + github.com/WwZzz/easyFL v0.0.0 // indirect + github.com/google-research/federated/tree/7525c36324cb022bc05c3fce88ef01147cae9740/periodic_distribution_shift v0.0.0 // indirect + github.com/Strange369/TypedDAG_on_HeteroMP v0.0.0 // indirect + github.com/YamingGuo98/FedIIR v0.0.0 // indirect + github.com/KarhouTam/Per-FedAvg v0.0.0 // indirect + github.com/songw-sw/f2l v0.0.0 // indirect + github.com/LatticeX-Foundation/Rosetta v0.0.0 // indirect + github.com/lokinko/Federated-Learning v0.0.0 // indirect + github.com/AmberLJC/FLsystem-paper v0.0.0 // indirect + github.com/liehe/byzantine-robust-noniid-optimizer v0.0.0 // indirect + github.com/IBM/probabilistic-federated-neural-matching v0.0.0 // indirect + github.com/LipingYi/FedGH v0.0.0 // indirect + github.com/zkhku/fedsage v0.0.0 // indirect + github.com/IBM/federated-learning-lib/blob/main/docs/papers.md v0.0.0 // indirect + github.com/trucndt/ami v0.0.0 // indirect + github.com/orionw/multilingual-federated-learning v0.0.0 // indirect + github.com/secretflow/secretflow v0.0.0 // indirect + github.com/google-research/federated/tree/master/gans v0.0.0 // indirect + github.com/PretomRoy/Defense-against-grad-inversion-attacks v0.0.0 // indirect + github.com/zlijingtao/ResSFL v0.0.0 // indirect + github.com/mtang724/Self-Balancing-Federated-Learning v0.0.0 // indirect + github.com/BHui97/PrivateFL v0.0.0 // indirect + github.com/carbonati/fl-zoo v0.0.0 // indirect + github.com/cuhksz-nlp/ASA-TM v0.0.0 // indirect + github.com/HewlettPackard/swarm-learning/blob/master/docs/videos.md v0.0.0 // indirect + github.com/sarapieri/fed_het v0.0.0 // indirect + github.com/SEED-VT/FedDebug v0.0.0 // indirect + github.com/alshedivat/fedpa v0.0.0 // indirect + github.com/Koukyosyumei/NAIST-FedML-Experiments v0.0.0 // indirect + github.com/visitworld123/fedfed v0.0.0 // indirect + github.com/jedmills/fedgbo v0.0.0 // indirect + github.com/shenzebang/Federated-Learning-Pytorch v0.0.0 // indirect + github.com/AI-secure/FedGame v0.0.0 // indirect + github.com/lingjuanlv/FPPDL v0.0.0 // indirect + github.com/balanced-fl/Addressing-Class-Imbalance-FL v0.0.0 // indirect + github.com/mc-nya/FedNest v0.0.0 // indirect + github.com/debcaldarola/fedsam v0.0.0 // indirect + github.com/rdz98/fedrecattack v0.0.0 // indirect + github.com/nusdbsystem/pivot v0.0.0 // indirect + github.com/konstmish/rr_prox_fed v0.0.0 // indirect + github.com/litian96/ditto v0.0.0 // indirect + github.com/MediaBrain-SJTU/FedDisco v0.0.0 // indirect + github.com/Hanzhouu/FedBFPT v0.0.0 // indirect + github.com/cyrilli/Async-LinUCB v0.0.0 // indirect + github.com/kiddyboots216/CommEfficient v0.0.0 // indirect + github.com/IBM/flexfl v0.0.0 // indirect + github.com/ljaiverson/pFL-APPLE v0.0.0 // indirect + github.com/lunanbit/FedUL v0.0.0 // indirect + github.com/HikariX/MP-FedXGB v0.0.0 // indirect + github.com/CharlieDinh/pFedMe v0.0.0 // indirect + github.com/jianyizhang123/FLOP v0.0.0 // indirect + github.com/FederatedAI/FATE/tree/master/python/federatedml/ensemble/secureboost v0.0.0 // indirect + github.com/google-research/federated/tree/master/generalization v0.0.0 // indirect + github.com/TL-System/plato/ v0.0.0 // indirect + github.com/FederalLab/OpenFed v0.0.0 // indirect + github.com/yxdyc/pfedgate v0.0.0 // indirect + github.com/BUAA-CST/iLRG v0.0.0 // indirect + github.com/bokun-wang/moml v0.0.0 // indirect + github.com/HaifengXia/PSE v0.0.0 // indirect + github.com/illidanlab/SplitMix v0.0.0 // indirect + github.com/Xtra-Computing/NIID-Bench v0.0.0 // indirect + github.com/littlesunlxy/fedpu-torch v0.0.0 // indirect + github.com/AffectFAL/AffectFAL v0.0.0 // indirect + github.com/xiyuanyang45/DynamicPFL v0.0.0 // indirect + github.com/ahmedcs/refl v0.0.0 // indirect + github.com/yuxuanzhang0713/fedcsr v0.0.0 // indirect + github.com/haoyangliASTAPLE/3DFed v0.0.0 // indirect + github.com/Kthyeon/ssfod v0.0.0 // indirect + github.com/sail-research/iba v0.0.0 // indirect + github.com/liecn/PyramidFL v0.0.0 // indirect + github.com/Chain123/Meta-HAR v0.0.0 // indirect + github.com/jhcknzzm/Federated-Learning-Backdoor/ v0.0.0 // indirect + github.com/vaseline555/superfed v0.0.0 // indirect + github.com/google-research/federated v0.0.0 // indirect + github.com/IBM/federated-learning-lib v0.0.0 // indirect + github.com/wanglun1996/secure-robust-federated-learning v0.0.0 // indirect + github.com/lowya/private-federated-learning-without-a-trusted-server v0.0.0 // indirect + github.com/Raymw/Federated-XGBoost v0.0.0 // indirect + github.com/FangXiuwen/AugHFL v0.0.0 // indirect + github.com/layer6ai-labs/ProxyFL v0.0.0 // indirect + github.com/flair-thu/creamfl v0.0.0 // indirect + github.com/chandra2thapa/SplitFed-When-Federated-Learning-Meets-Split-Learning v0.0.0 // indirect + github.com/Princeton-SysML/FILM v0.0.0 // indirect + github.com/litian96/FedProx v0.0.0 // indirect + github.com/REIYANG/FedBCD v0.0.0 // indirect + github.com/xidongwu/Federated-Minimax-and-Conditional-Stochastic-Optimization/tree/main v0.0.0 // indirect + github.com/aioz-ai/MultigraphFL v0.0.0 // indirect + github.com/nju-websoft/FedLU v0.0.0 // indirect + github.com/AllenBeau/pFedBayes v0.0.0 // indirect + github.com/AI-secure/FLBenchmark-toolkit v0.0.0 // indirect + github.com/youngfish42/FL-paper-update-tracker v0.0.0 // indirect + github.com/a514514772/ProgFed v0.0.0 // indirect + github.com/TinfoilHat0/Defending-Against-Backdoors-with-Robust-Learning-Rate v0.0.0 // indirect + github.com/SMILELab-FL/FedLab-benchmarks v0.0.0 // indirect + github.com/baowenxuan/ATP v0.0.0 // indirect + github.com/zexilee/icml-2023-fedlaw v0.0.0 // indirect + github.com/alibaba/FederatedScope/tree/FSreal v0.0.0 // indirect + github.com/Xtra-Computing/PrivML v0.0.0 // indirect + github.com/chunmeifeng/FedPR v0.0.0 // indirect + github.com/alibaba/FederatedScope/tree/master/benchmark/FedHPOBench v0.0.0 // indirect + github.com/sunjunaimer/TPAMI-LAQ v0.0.0 // indirect + github.com/DianboWork/FedDS v0.0.0 // indirect + github.com/Rachelxuan11/FLAME v0.0.0 // indirect + github.com/baowenxuan/fedcollab v0.0.0 // indirect + github.com/cuis15/learning-to-collaborate v0.0.0 // indirect + github.com/zj-jayzhang/Federated-Class-Continual-Learning v0.0.0 // indirect + github.com/SMILELab-FL/FedLab v0.0.0 // indirect + github.com/MediaBrain-SJTU/FedDG-GA v0.0.0 // indirect + github.com/rasmus-pagh/private-countsketch v0.0.0 // indirect + github.com/daizhongxiang/Federated_Bayesian_Optimization v0.0.0 // indirect + github.com/intel/openfl v0.0.0 // indirect + github.com/South-hw/FedPara_ICLR22 v0.0.0 // indirect + github.com/royson/fedl2p/ v0.0.0 // indirect + github.com/liyipeng00/convergence v0.0.0 // indirect + github.com/facebookresearch/canife v0.0.0 // indirect + github.com/GOGODD/FL-EDGE-COMPUTING/releases/tag/federated_learning v0.0.0 // indirect + github.com/zhaohaoru/federated-clustering-of-bandits v0.0.0 // indirect + github.com/NVlabs/FedFomo v0.0.0 // indirect + github.com/FangXiuwen/Robust_FL v0.0.0 // indirect + github.com/wizard1203/VHL v0.0.0 // indirect + github.com/divyansh03/fedexp v0.0.0 // indirect + github.com/yuetan031/fedproto v0.0.0 // indirect + github.com/hongyouc/fedbe v0.0.0 // indirect + github.com/hongliny/sharp-bounds-for-fedavg-and-continuous-perspective v0.0.0 // indirect + github.com/MingruiLiu-ML-Lab/episode_plusplus v0.0.0 // indirect + github.com/wnma3mz/FedLMD v0.0.0 // indirect + github.com/arodio/ca-fed v0.0.0 // indirect + github.com/albietz/ppsgd v0.0.0 // indirect + github.com/amitport/EDEN-Distributed-Mean-Estimation v0.0.0 // indirect + github.com/qizhuang-qz/FedCSPC v0.0.0 // indirect + github.com/anishacharya/DeLiCoCo v0.0.0 // indirect + github.com/osu-nlp-group/fl4semanticparsing v0.0.0 // indirect + github.com/kaiyuanmifen/FederatedNLP v0.0.0 // indirect + github.com/dual-grp/fedu_fmtl v0.0.0 // indirect + github.com/Distributed-Learning-Networking-Group/FedMoS/ v0.0.0 // indirect + github.com/JonasGeiping/invertinggradients v0.0.0 // indirect + github.com/FederatedAI/research/tree/main/publications/FedCG v0.0.0 // indirect + github.com/LTTM/FedSpace v0.0.0 // indirect + github.com/deu30303/feddefender v0.0.0 // indirect + github.com/shahakash28/simc v0.0.0 // indirect + github.com/alibaba-edu/mpc4j/tree/main/mpc4j-sml-opboost v0.0.0 // indirect + github.com/FedML-AI/FedGraphNN v0.0.0 // indirect + github.com/innovation-cat/Awesome-Federated-Machine-Learning v0.0.0 // indirect + github.com/KAI-YUE/rog v0.0.0 // indirect + github.com/corentingiraud/federated-learning-secure-aggregation v0.0.0 // indirect + github.com/IBM/FedMA v0.0.0 // indirect + github.com/yuetan031/fedstar v0.0.0 // indirect + github.com/Hypervoyager/PFL v0.0.0 // indirect + github.com/facebookresearch/where_to_begin v0.0.0 // indirect + github.com/rong-dai/DisPFL v0.0.0 // indirect + github.com/xidongwu/Federated-Minimax-and-Conditional-Stochastic-Optimization/ v0.0.0 // indirect + github.com/omarfoq/communication-in-cross-silo-fl v0.0.0 // indirect + github.com/OpenMined/PyVertical v0.0.0 // indirect + github.com/ml-unito/federation_boosting v0.0.0 // indirect + github.com/NVIDIA/NVFlare v0.0.0 // indirect + github.com/jeremy313/FL-WBC v0.0.0 // indirect + github.com/ebagdasa/backdoor_federated_learning v0.0.0 // indirect + github.com/med-air/FedBN v0.0.0 // indirect + github.com/SaraBabakN/MFCL-NeurIPS23 v0.0.0 // indirect + github.com/ljaiverson/pgfed v0.0.0 // indirect + github.com/pierreHmbt/FedCP-QQ v0.0.0 // indirect + github.com/CGCL-codes/pFedSD v0.0.0 // indirect + github.com/aelgabli/FedNew v0.0.0 // indirect + github.com/SkellamMixtureMechanism/SMM v0.0.0 // indirect + github.com/hyhmia/DisTrans v0.0.0 // indirect + github.com/Ruiquan5514/Federated-Linear-Contextual-Bandits v0.0.0 // indirect + github.com/saist1993/dpnlp v0.0.0 // indirect + github.com/OpenMined/SyferText v0.0.0 // indirect + github.com/Emory-AIMS/PFA v0.0.0 // indirect + github.com/xmed-lab/rscfed v0.0.0 // indirect + github.com/KaiyuanZh/FLIP v0.0.0 // indirect + github.com/garyzhang99/DM-PFL v0.0.0 // indirect + github.com/nds2022/SGBoost v0.0.0 // indirect + github.com/AfoninAndrei/ICLR2022 v0.0.0 // indirect + github.com/mmendiet/FedAlign v0.0.0 // indirect + github.com/xu-jingyi/fedcorr v0.0.0 // indirect + github.com/KAI-YUE/ntk-fed v0.0.0 // indirect + github.com/FedML-AI/FedNLP v0.0.0 // indirect + github.com/gingsmith/fmtl v0.0.0 // indirect + github.com/bingzhaozhu/xtab v0.0.0 // indirect + github.com/TCtower/GlueFL v0.0.0 // indirect + github.com/haoyuzhao123/coreset-vfl-codes v0.0.0 // indirect + github.com/ignavierng/notears-admm v0.0.0 // indirect + github.com/youngfish42/Awesome-FL/issues v0.0.0 // indirect + github.com/SMILELab-FL/FedLegal v0.0.0 // indirect + github.com/Xtra-Computing/FedSim v0.0.0 // indirect + github.com/chaoyanghe/Awesome-Federated-Learning v0.0.0 // indirect + github.com/gcfgae/GCFGAE v0.0.0 // indirect + github.com/jiayunz/fedalign v0.0.0 // indirect )