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title: 'DIANNA: Deep Insight And Neural Network Analysis' tags: - Python - explainable AI - deep neural networks - ONNX - benchmark sets authors: - name: Elena Ranguelova^[co-first author] # note this makes a footnote saying 'co-first author' orcid: 0000-0002-9834-1756 affiliation: 1 - name:…
The main features of dianna-ai/dianna 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.
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
