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

pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized

Graph Stochastic Attention (GSAT) The official implementation of GSAT for our paper: Interpretable and Generalizable Graph Learning via Stochastic Att

Shapley Explanation Networks Implementation of the paper "Shapley Explanation Networks" at ICLR 2021. Note that this repo heavily uses the experimenta

Currently a Beta-Version lucidmode is an open-source, low-code and lightweight Python framework for transparent and interpretable machine learning mod