Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
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Updated
Oct 19, 2024 - Python
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
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
✨ AI-powered coding, seamlessly in Neovim. Supports Anthropic, Copilot, Gemini, Ollama, OpenAI and xAI LLMs
Interesting resources related to XAI (Explainable Artificial Intelligence)
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
H2O.ai Machine Learning Interpretability Resources
Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ [email protected]
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