There are 2 repositories under black-box topic.
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
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
[EMNLP'24] MedAdapter: Efficient Test-Time Adaptation of Large Language Models Towards Medical Reasoning
Simple grammar-based test case generator
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.
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
Bootplot is a package for black-box uncertainty visualization.
The main VAMOS repository
Togomori is a comprehensive solution for web applications reconnaissance designed to simplify the process of information gathering and data visualization.
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
Black box testing using different tools for the Facebook website to find bugs and make test cases.
Identificazione, Controllo, Simulazione di un robot SCARA con smorzatori e molle
Pytorch Implementation of SemiAdv.
Black Box Interpretability in R
The concept of Black Box is mainly heard by us in case of Aero-planes. Upon a catastrophe the Black Box is used to analyze the root cause of the issue. However, the purpose of Black Box can go beyond catastrophe analysis.
Research on Material Science using Neural Networks black box approach
Finding the best solution for geometry of electrical devices based on defined target for frequency responses
Deep dive into Spark UDFs' characteristics.
A reference implementation of non-functional black-box performance benchmarking ⚫ for ROS 2
Collection of efficient and optimized algorithms and data structures in C++ for competitive programming, serving as a centralized hub for solving problems on platforms like CodeForces and more.
Teleològic i abductiu: Una aproximació als models additius per la interpretabilitat.
Audio Player JS package