Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
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Updated
Aug 29, 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.
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
Algorithms for explaining machine learning models
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
A collection of research materials on explainable AI/ML
Generate Diverse Counterfactual Explanations for any machine learning model.
XAI - An eXplainability toolbox for machine learning
moDel Agnostic Language for Exploration and eXplanation
Interesting resources related to XAI (Explainable Artificial Intelligence)
H2O.ai Machine Learning Interpretability Resources
Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
A curated list of awesome Fairness in AI resources
Papers about explainability of GNNs
Layer-wise Relevance Propagation (LRP) for LSTMs.
Repository for the Explainable Deep One-Class Classification paper
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 @ ms8909@nyu.edu
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