Rule-based Representation Learner This is a PyTorch implementation of Rule-based Representation Learner (RRL) as described in NeurIPS 2021 paper: Scal

A collection of research papers and software related to explainability in graph machine learning.

XAI - An eXplainability toolbox for machine learning XAI is a Machine Learning library that is designed with AI explainability in its core. XAI contai

AI Explainability 360 (v0.2.1) The AI Explainability 360 toolkit is an open-source library that supports interpretability and explainability of datase

🎉 What's new ? Version New Feature Description Tutorial 1.6.x Explainability Quality Metrics To help increase confidence in explainability methods, y

Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The

Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The

CARLA - Counterfactual And Recourse Library CARLA is a python library to benchmark counterfactual explanation and recourse models. It comes out-of-the

Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. 📚 docs • 📖 demo notebooks Modern

👋🦊 Xplique is a Python toolkit dedicated to explainability, currently based on Tensorflow.

Documentation | Paper [JMLR] | Tutorials | Benchmarks | Examples DIG: Dive into Graphs is a turnkey library for graph deep learning research. Why DIG?

MindsDB is an open-source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning

moDel Agnostic Language for Exploration and eXplanation Overview Unverified black box model is the path to the failure. Opaqueness leads to distrust.

Interpretable Control Exploration and Counterfactual Explanation (ICE) on StyleGAN Which Style Makes Me Attractive? Interpretable Control Discovery an

Responsible AI Workshop Responsible innovation is top of mind. As such, the tech industry as well as a growing number of organizations of all kinds in

ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any model or data and different Shapley Values for tree-based mod

hyperbox-brain is a Python open source toolbox implementing hyperbox-based machine learning algorithms built on top of scikit-learn and is distributed