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.

Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"

Official Implementation of Unweighted Data Subsampling via Influence Function - AAAI 2020

Influence Estimation for Gradient-Boosted Decision Trees

A simple PyTorch implementation of influence functions.

pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation

Influence Functions with (Eigenvalue-corrected) Kronecker-Factored Approximate Curvature

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.

👋 Influenciae is a Tensorflow Toolbox for Influence Functions

Data-efficient Fine-tuning for LLM-based Recommendation (SIGIR'24)

[CVPR 2023] Regularizing Second-Order Influences for Continual Learning

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.

This is an implementation of the paper ”Interpreting Twitter User Geolocation“.

Time series data contribution via influence functions

This repo provides an implementation of the paper Interpreting Twitter User Geolocation.

[EMNLP-2022 Findings] Code for paper “ProGen: Progressive Zero-shot Dataset Generation via In-context Feedback”.

A simple Jax implementation of influence functions.