Influence Functions with (Eigenvalue-corrected) Kronecker-Factored Approximate Curvature
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Updated
Jul 13, 2024 - Python
Influence Functions with (Eigenvalue-corrected) Kronecker-Factored Approximate Curvature
pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation
A simple PyTorch implementation of influence functions.
Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"
Influence Estimation for Gradient-Boosted Decision Trees
Official implementation of "Deeper Understanding of Black-box Predictions via Generalized Influence Functions".
👋 Influenciae is a Tensorflow Toolbox for Influence Functions
Intriguing Properties of Data Attribution on Diffusion Models (ICLR 2024)
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.
This is an implementation of the paper ”Interpreting Twitter User Geolocation“.
This repo provides an implementation of the paper Interpreting Twitter User Geolocation.
[CVPR 2023] Regularizing Second-Order Influences for Continual Learning
A brief notebook on Influence Function (IF) for classical generative models (e.g., k-NN, KDE, GMM)
[EMNLP-2022 Findings] Code for paper “ProGen: Progressive Zero-shot Dataset Generation via In-context Feedback”.
An Empirical Study of Memorization in NLP (ACL 2022)
This is a [Stable] PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence Functions by Pang Wei Koh and Percy Liang.
Official Implementation of Unweighted Data Subsampling via Influence Function - AAAI 2020
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.
Tiny Tutorial on https://arxiv.org/abs/1703.04730
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