DIANNA
DIANNA: Deep Insight And Neural Network Analysis - Published in JOSS (2022)
TSInterpret
TSInterpret: A Python Package for the Interpretability of Time Series Classification - Published in JOSS (2023)
https://github.com/ajayarunachalam/msda
Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector
talktomodel
TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!
https://github.com/astrazeneca/awesome-shapley-value
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
dianna-exploration
This repository contains the expliratory and research work from the DIANNA project
b-cosification
[NeurIPS 2024] Code for the paper: B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable.
https://github.com/cair/fast-tsetlin-machine-in-cuda-with-imdb-demo
A CUDA implementation of the Tsetlin Machine based on bitwise operators
credit-risk-explainability
Credit Risk Explainability is an open-source implementation of the research paper: "An Explainable AI Framework for Credit Evaluation and Analysis" (Applied Soft Computing Journal, 2024).