Research on Material Science using Neural Networks black box approach
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Updated
Jul 17, 2023 - Python
Research on Material Science using Neural Networks black box approach
A reference implementation of non-functional black-box performance benchmarking ⚫ for ROS 2
AI Explanation methods based on coalitional game theory, to explain any machine learning prediction.
Bootplot is a package for black-box uncertainty visualization.
Pytorch Implementation of SemiAdv.
Togomori is a comprehensive solution for web applications reconnaissance designed to simplify the process of information gathering and data visualization.
Retrospective Extraction of Visual and Logical Insights for Ontology-based interpretation of Neural Networks
Black-box Few-shot Knowledge Distillation
Model explanation provides the ability to interpret the effect of the predictors on the composition of an individual score.
[NeurIPS'20] Learning Black-Box Attackers with Transferable Priors and Query Feedback
Simplicial Homology Global Optimization
code for our CVPR 2022 paper "DINE: Domain Adaptation from Single and Multiple Black-box Predictors"
A Python module for parallel optimization of expensive black-box functions
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
moDel Agnostic Language for Exploration and eXplanation
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