interpretability
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A game theoretic approach to explain the output of any machine learning model.
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May 1, 2025 - Jupyter Notebook
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
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May 1, 2025
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
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Apr 7, 2025 - Python
Fit interpretable models. Explain blackbox machine learning.
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Apr 25, 2025 - C++
Model interpretability and understanding for PyTorch
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May 2, 2025 - Python
A collection of infrastructure and tools for research in neural network interpretability.
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Feb 6, 2023 - Jupyter Notebook
A curated list of awesome responsible machine learning resources.
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Apr 17, 2025
StellarGraph - Machine Learning on Graphs
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Apr 10, 2024 - Python
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
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Apr 25, 2025 - Jupyter Notebook
Algorithms for explaining machine learning models
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Apr 4, 2025 - Python
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
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May 2, 2025 - Python
FedML - The Research and Production Integrated Federated Learning Library:https://fedml.ai
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Sep 3, 2022
A JAX research toolkit for building, editing, and visualizing neural networks.
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Apr 26, 2025 - Python
[ICCV 2017] Torch code for Grad-CAM
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Sep 17, 2022 - Lua
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.
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Feb 7, 2025 - TypeScript
A collection of research materials on explainable AI/ML
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Mar 21, 2025 - Markdown
Stanford NLP Python library for Representation Finetuning (ReFT)
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Feb 6, 2025 - Python
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
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Mar 5, 2025 - Jupyter Notebook
moDel Agnostic Language for Exploration and eXplanation
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Feb 12, 2025 - Python
Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
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Aug 30, 2023 - Jupyter Notebook
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