Riemannian Adaptive Optimization Methods with pytorch optim
-
Updated
Apr 28, 2024 - Python
Riemannian Adaptive Optimization Methods with pytorch optim
A C++ library of Markov Chain Monte Carlo (MCMC) methods
Regression Graph Neural Network (regGNN) for cognitive score prediction.
Riemannian stochastic optimization algorithms: Version 1.0.3
Implementation of Deep SPDNet in pytorch
Measure the distance between two spectra/signals using optimal transport and related metrics
Riemannian metrics to measure distances in latent space of VAEs
Dimensionality reduction on manifold of SPD matrices, based on pymanopt implementation
Sensitivity Analysis of Deep Neural Networks (AAAI-19 paper)
C++ library for meshes and finite elements on manifolds
Subsampled Riemannian trust-region (RTR) algorithms
Matlab implementation of paper "Principal Geodesic Analysis in the Space of Discrete Shells", SGP-2018
The code for vector transport free LBFGS quasi-Newton's optimization on the Riemannian manifolds
Project in Advanced Robotics course project at SDU 21/22. Implementation of learning method for skills for arm robots based on GMM with Rieamannian Manifolds
A package providing tractable examples of parallel transport for several matrix manifolds
Implementing the algorithms of Kim et al. 2014 for regressing multiple symmetric positive definite matrices against real valued covariates.
Essential Books for Computer Science
GitHub repository for ”Learning a Discriminative Grassmannian Neural Network for Visual Classification“
Code implementations of the methods discussed in Generalized Fiducial Inference on Differentiable Manifolds by A. Murph, J. Hannig, and J. Williams.
Add a description, image, and links to the riemannian-manifold topic page so that developers can more easily learn about it.
To associate your repository with the riemannian-manifold topic, visit your repo's landing page and select "manage topics."