moDel Agnostic Language for Exploration and eXplanation

An automatic obfuscation tool for Android apps that works in a black-box fashion, supports advanced obfuscation features and has a modular architecture easily extensible with new techniques

A Python module for parallel optimization of expensive black-box functions

Yet another black-box optimization library for Python

code for our CVPR 2022 paper "DINE: Domain Adaptation from Single and Multiple Black-box Predictors"

Simplicial Homology Global Optimization

[NeurIPS'20] Learning Black-Box Attackers with Transferable Priors and Query Feedback

Simple grammar-based test case generator

[EMNLP'24] MedAdapter: Efficient Test-Time Adaptation of Large Language Models Towards Medical Reasoning

Design and Cryptanalysis of Symmetric-Key Algorithms in Black and White-box Models

MAD教程·模仿篇：仿黑盒。

Adaptive stress testing of black-box systems within POMDPs.jl

Model explanation provides the ability to interpret the effect of the predictors on the composition of an individual score.

Black-box Few-shot Knowledge Distillation

A set of reactor design benchmark problems to evaluate high-dimensional, expensive, and potentially multi-fidelity optimisation algorithms.

Implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation (Fong, et. al., 2018)

Retrospective Extraction of Visual and Logical Insights for Ontology-based interpretation of Neural Networks

The main VAMOS repository

AI Explanation methods based on coalitional game theory, to explain any machine learning prediction.

This repository contains code and documentation for performing black box testing and graph coverage analysis on software systems. Black box testing is a technique that tests the functionality of a system without knowing its internal structure or implementation. Graph coverage analysis is a technique that measures how well a set of test cases covers