Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

Fit interpretable models. Explain blackbox machine learning.

A curated list of awesome responsible machine learning resources.

Algorithms for explaining machine learning models

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

Interpretability and explainability of data and machine learning models

✨ AI-powered coding, seamlessly in Neovim

A collection of research materials on explainable AI/ML

moDel Agnostic Language for Exploration and eXplanation

Generate Diverse Counterfactual Explanations for any machine learning model.

XAI - An eXplainability toolbox for machine learning

Interesting resources related to XAI (Explainable Artificial Intelligence)

BaseAI — The Web AI Framework. The easiest way to build serverless autonomous AI agents with memory. Start building local-first, agentic pipes, tools, and memory. Deploy serverless with one command.

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

Papers about explainability of GNNs

👋 Xplique is a Neural Networks Explainability Toolbox

Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations

ComfyUI-IF_AI_tools is a set of custom nodes for ComfyUI that allows you to generate prompts using a local Large Language Model (LLM) via Ollama. This tool enables you to enhance your image generation workflow by leveraging the power of language models.

H2O.ai Machine Learning Interpretability Resources