This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence Functions by Pang Wei Koh and Percy Liang.
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Oct 29, 2023 - Python
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influence-functions
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Influence Functions with (Eigenvalue-corrected) Kronecker-Factored Approximate Curvature
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Jun 24, 2025 - Python
pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation
machine-learning game-theory data-cleaning data-quality banzhaf-index influence-functions robust-machine-learning shapley-value data-valuation data-centric-ai transferlab least-core data-pruning
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May 10, 2025 - Python
A simple PyTorch implementation of influence functions.
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Jun 17, 2024 - Python
Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"
python machine-learning paper machine-learning-algorithms gradient-boosting catboost influence-functions
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May 28, 2024 - Python
Official Implementation of Unweighted Data Subsampling via Influence Function - AAAI 2020
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Apr 14, 2021 - Python
👋 Influenciae is a Tensorflow Toolbox for Influence Functions
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Apr 18, 2024 - Python
Data-efficient Fine-tuning for LLM-based Recommendation (SIGIR'24)
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Feb 21, 2025 - Python
[CVPR 2023] Regularizing Second-Order Influences for Continual Learning
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May 19, 2023 - Python
Intriguing Properties of Data Attribution on Diffusion Models (ICLR 2024)
attribution interpretability influence-functions diffusion-models ddpm data-valuation data-centric-ai stable-diffusion data-attribution
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Jan 23, 2024 - Jupyter Notebook
Influence Estimation for Gradient-Boosted Decision Trees
interpretability influence-functions gradient-boosted-trees boostin explainability tracin instance-based influence-estimation instance-attribution influential-examples
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May 27, 2024 - Python
[EMNLP-2022 Findings] Code for paper “ProGen: Progressive Zero-shot Dataset Generation via In-context Feedback”.
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Feb 4, 2023 - Python
This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence Functions by Pang Wei Koh and Percy Liang.
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Updated
Jun 20, 2020 - Python
Tiny Tutorial on https://arxiv.org/abs/1703.04730
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Nov 19, 2019 - Jupyter Notebook
An Empirical Study of Memorization in NLP (ACL 2022)
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Jun 22, 2022 - Jupyter Notebook
Time series data contribution via influence functions
time-series time-series-forecasting influence-functions time-series-anomaly-detection data-valuation
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Jan 18, 2025 - Python
Official implementation of "Deeper Understanding of Black-box Predictions via Generalized Influence Functions".
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Dec 5, 2024 - Jupyter Notebook
This is an implementation of the paper ”Interpreting Twitter User Geolocation“.
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Jul 6, 2023 - Python
A brief notebook on Influence Function (IF) for classical generative models (e.g., k-NN, KDE, GMM)
kde numpy gaussian-mixture-models gmm k-nearest-neighbours kernel-density-estimation interpretability k-nearest-neighbors influence-functions interpretable-machine-learning k-nearest-neighbors-k-nn self-influence-functions instance-based-interpretability
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Feb 6, 2023 - Jupyter Notebook
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