NeuroX provide all the necessary tooling to perform Interpretation and Analysis of (Deep) Neural Networks centered around Probing. Specifically, the toolkit provides:
Las características principales de fdalvi/neurox son: Explainable AI Libraries.
Las alternativas de código abierto para fdalvi/neurox incluyen: 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.
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
