treemind

A game theoretic approach to explain the output of any machine learning model.

? Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

Algorithms for explaining machine learning models

Evaluation and Tracking for LLM Experiments

Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)

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

A library for graph deep learning research

A JAX research toolkit for building, editing, and visualizing neural networks.

Interpretability and explainability of data and machine learning models

[ICCV 2017] Torch code for Grad-CAM