explainable-ai

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

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.

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

Debugging, monitoring and visualization for Python Machine Learning and Data Science

High-Performance Symbolic Regression in Python and Julia

Generative AI SDK for Web to create AI Agents for apps built with JavaScript, React, Angular, Vue, Ember, Electron

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

Interpretability and explainability of data and machine learning models

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

A collection of research materials on explainable AI/ML

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

moDel Agnostic Language for Exploration and eXplanation

Generate Diverse Counterfactual Explanations for any machine learning model.

Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

XAI - An eXplainability toolbox for machine learning

ICCV 2023 Papers: Discover cutting-edge research from ICCV 2023, the leading computer vision conference. Stay updated on the latest in computer vision and deep learning, with code included. ⭐ support visual intelligence development!

Explainability for Vision Transformers

OmniXAI: A Library for eXplainable AI