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
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).
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.
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)