npm · PyPI
meta-pytorch/captum
Model interpretability and understanding for PyTorch
BSD-3-Clause28. Aug. 2026 · Metriken 2.10.0
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#interpretability
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9 Einträge
PyPI · npm
shap/shap
A game theoretic approach to explain the output of any machine learning model.
MIT5. Aug. 2026 · Metriken 2.10.0
PyPI
mmschlk/shapiq
Shapley Interactions and Shapley Values for Machine Learning
MIT26. Juli 2026 · Metriken 2.10.0
npm · PyPI
interpretml/interpret
Fit interpretable models. Explain blackbox machine learning.
MIT12. Aug. 2026 · Metriken 2.10.0
PyPI
givasile/effector
Effector - a Python package for global and regional effect methods
MIT17. Juli 2026 · Metriken 2.10.0
PyPI
fathom-lab/styxx
Verification for the agent era. Your coding agent's PR summary cannot lie about its diff - one CI line. Plus the research: the first map of which AI minds can read each other. Every claim machine-verified against committed receipts, negatives included. pip install styxx
MIT19. Aug. 2026 · Metriken 2.10.0
PyPI
Sid-MB/interlens
Python framework for efficient and precise interpretability research on multi-agent conversations.
AGPL-3.015. Juli 2026 · Metriken 2.10.0
PyPI
rmovva/HypotheSAEs
HypotheSAEs: hypothesizing interpretable relationships in text datasets using sparse autoencoders. https://arxiv.org/abs/2502.04382
Apache-2.027. Juli 2026 · Metriken 2.10.0
PyPI
srikumar2050/hugiml-core
High-performance interpretable ML classifier using High Utility Gain patterns (IEEE Access 2024). C++ accelerated, scikit-learn compatible, with EBM-style explanations, adaptive binning, pattern pruning, and deployment tooling for regulated domains.
Eigene Lizenz19. Juli 2026 · Metriken 2.10.0