Popular GitHub Repositories for Explanation

A curated list of the latest breakthroughs in AI (in 2022) by release date with a clear video explanation, link to a more in-depth article, and code.

A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.

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

A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and?code

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion

NFNets and Adaptive Gradient Clipping for SGD implemented in PyTorch. Find explanation at tourdeml.github.io/blog/

CorEx or "Correlation Explanation" discovers a hierarchy of informative latent factors. This reference implementation has been superseded by other versions below.

A curated list of the latest breakthroughs in AI (in 2023) by release date with a clear video explanation, link to a more in-depth article, and code.

Step by step explanation/tutorial of llama2.c

Final Year Fake News Detection using Machine learning Project with Report, PPT, Code, Research Paper, Documents and Video Explanation.

Pytorch Implementation of recent visual attribution methods for model interpretability

GPTs for ComfyUI | Explanation Creation Resolution | ComfyUI 助手

TalkToModel gives anyone with the powers of XAI through natural language conversations ?!

A nvim plugin Powered by GPT4ALL for Real-time Code Explanation and Vulnerability Detection (no internet necessary)

Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)

Multivariate Anomaly Detection with Interpretability (MADI) published in ICML 2020

Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.

Generating and validating natural-language explanations for the brain.

AnswerGit is a platform that allows you to analyze Git repositories and ask AI questions about the code. It uses AI to provide detailed explanations and summaries of Git commands, workflows, and code structure, making it easier to understand and interact with code repositories.