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interpretable-ml · GitHub Topics · GitHub

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interpretable-ml

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Model interpretability and understanding for PyTorch

  • Updated Aug 19, 2026
  • Python

Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/

  • Updated May 23, 2021
  • Python

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

  • Updated Jun 17, 2024
  • Jupyter Notebook

Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.

  • Updated May 13, 2026
  • Python

The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification" and TPAMI paper "Learning Interpretable Rules for Scalable Data Representation and Classification"

  • Updated Mar 12, 2024
  • Python

[NeurIPS 2023] This is the official code for the paper "TPSR: Transformer-based Planning for Symbolic Regression"

  • Updated Nov 4, 2024
  • Python

The most comprehensive XRL paper list: 277 papers (2016–2026) on interpretable and explainable RL. Surveys, saliency, counterfactuals, policy summarization and more.

  • Updated Apr 4, 2026

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