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A toolbox to iNNvestigate neural networks' predictions!
This repository contains a sample implementation of Gradient Feature Auditing (GFA) meant to be generalizable to most datasets. For more information on the repair process, see our paper on Certifying and Removing Disparate Impact. For information on the full auditing process, see our paper on…
Project Page // Paper // No-code Web Demo // Colab Notebook
🦊 Xplique (pronounced \ɛks.plik\ ) is a Python toolkit dedicated to explainability. The goal of this library is to gather the state of the art of Explainable AI to help you understand your complex neural network models. Originally built for Tensorflow's model it also works for PyTorch models…
The main features of deel-ai/xplique are: Explainable AI Libraries.
Projects with overlapping indexed features include: albermax/innvestigate — A toolbox to iNNvestigate neural networks' predictions! algofairness/blackboxauditing — This repository contains a sample implementation of Gradient Feature Auditing (GFA) meant to be generalizable to most… alvinwan/neural-backed-decision-trees — Project Page // Paper // No-code Web Demo // Colab Notebook. andosa/treeinterpreter — TreeInterpreter. ankurtaly/integrated-gradients — (a.k.a. Path-Integrated Gradients, a.k.a. Axiomatic Attribution for Deep Networks). aerdem4/lofo-importance — Leave One Feature Out Importance.
