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jphall663 / interpretable_machine_learning_with_python

Star 683

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

python data-science machine-learning data-mining h2o gradient-boosting-machine transparency decision-tree fairness lime accountability interpretability interpretable-ai interpretable-ml xai fatml interpretable interpretable-machine-learning iml machine-learning-interpretability
  • Updated Jun 17, 2024
  • Jupyter Notebook

hans66hsu / nn_interpretability

Star 119

Pytorch implementation of various neural network interpretability methods

pytorch deepdream saliency-map occlusion-sensitivity smoothgrad guided-backpropagation interpretable-deep-learning lrp gradient-visualization interpretable gradcam deconvnet cnn-visualization deeplift integrated-gradients activation-maximization interpretability-methods uncertainty-interpretability taylor-decomposition nn-interpretability
  • Updated Mar 8, 2022
  • Jupyter Notebook

pauljblazek / deepdistilling

Star 104

Mechanistically interpretable neurosymbolic AI (Nature Comput Sci 2024): losslessly compressing NNs to computer code and discovering new algorithms which generalize out-of-distribution and outperform human-designed algorithms

program-synthesis knowledge-distillation inductive-logic-programming domain-adaptation explainable-ai interpretable distilling neurosymbolic model-distillation out-of-distribution-generalization mechanistic-interpretability
  • Updated Feb 20, 2024
  • Python

rehmanzafar / xai-iml-sota

Star 76

Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.

machine-learning human-in-the-loop interpretability explainable-artificial-intelligence researchers interactive-machine-learning deep-learning-visualization human-in-the-loop-machine-learning explainable-ml xai interpretable interpretable-machine-learning iml model-interpretability explainable interpretable-models explainable-models interpretable-learning explaining-ai explanation-methods
  • Updated Sep 29, 2022
  • R

TheAxeC / behavior-aligned-ecog-transfer

Star 3

Behavior-supervised alignment for cross-subject neural decoding across non-corresponding ECoG electrode grids: align each patient's grid onto shared finger-motor axes defined by the decode target, then decode with a shared seq2seq TCN, interpretably and without a foundation model.

reproducible-research neuroscience transfer-learning brain-computer-interface ecog tcn interpretable cross-subject finger-movement neural-decoding
  • Updated Jul 6, 2026
  • Python

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