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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.
Created
2019-11-30
18 commits to master branch, last one 3 years ago
Influence Functions with (Eigenvalue-corrected) Kronecker-Factored Approximate Curvature
Created
2024-03-12
534 commits to main branch, last one 6 months ago
pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation
Created
2021-04-02
4,064 commits to develop branch, last one 7 hours ago
A simple PyTorch implementation of influence functions.
Created
2022-07-01
7 commits to main branch, last one 2 years ago
Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"
Created
2018-02-15
30 commits to master branch, last one 8 months ago
Official Implementation of Unweighted Data Subsampling via Influence Function - AAAI 2020
Created
2019-11-12
20 commits to master branch, last one 3 years ago
👋 Influenciae is a Tensorflow Toolbox for Influence Functions
Created
2021-10-04
193 commits to main branch, last one 9 months ago
[CVPR 2023] Regularizing Second-Order Influences for Continual Learning
Created
2023-02-28
7 commits to main branch, last one about a year ago
Intriguing Properties of Data Attribution on Diffusion Models (ICLR 2024)
Created
2023-11-01
4 commits to main branch, last one about a year ago