visual-attribution

A library for debugging/inspecting machine learning classifiers and explaining their predictions

FULL Implementation of RCNN from scratch

Framework for autonomous learning of explainable graph neural networks

A time series forecasting project from Kaggle that uses Seq2Seq + LSTM technique to forecast the headcounts. Detailed explanation on how the special neural network structure works is provided.

explainy is a Python library for generating machine learning model explanations for humans

This is the official PyTorch implementation of our NeurIPS 2021 paper: "SalKG: Learning From Knowledge Graph Explanations for Commonsense Reasoning"

Causality-Aware Local Interpretable Model Agnostic Explanations

ELIH: Explain Machine Learning predictions like I'm a human

[LREC2022] SuMe: A Dataset towards Summarizing biomedical Mechanisms

Explanation system for semi-supervised multi-objective optimization