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GitHub topics: influence-functions

jordandeklerk/pyDiD

Python package implementing a variety of modern DiD and doubly robust DiD estimators with diagnostic tools and sensitivity tests.

Language: Python - Size: 6.43 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 0 - Forks: 0

pomonam/kronfluence

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

Language: Python - Size: 21.9 MB - Last synced at: 2 days ago - Pushed at: 20 days ago - Stars: 156 - Forks: 21

nimarb/pytorch_influence_functions

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.

Language: Python - Size: 448 KB - Last synced at: 3 days ago - Pushed at: over 1 year ago - Stars: 335 - Forks: 73

sail-sg/D-TRAK

Intriguing Properties of Data Attribution on Diffusion Models (ICLR 2024)

Language: Jupyter Notebook - Size: 39.3 MB - Last synced at: 6 days ago - Pushed at: over 1 year ago - Stars: 31 - Forks: 3

aai-institute/pyDVL

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

Language: Python - Size: 436 MB - Last synced at: about 1 month ago - Pushed at: 2 months ago - Stars: 130 - Forks: 7

deel-ai/influenciae

đź‘‹ Influenciae is a Tensorflow Toolbox for Influence Functions

Language: Python - Size: 2.03 MB - Last synced at: 28 days ago - Pushed at: about 1 year ago - Stars: 63 - Forks: 5

alstonlo/torch-influence

A simple PyTorch implementation of influence functions.

Language: Python - Size: 6.94 MB - Last synced at: 3 months ago - Pushed at: about 1 year ago - Stars: 86 - Forks: 11

Linxyhaha/DEALRec

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

Language: Python - Size: 52.8 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 25 - Forks: 3

mintaywon/IF_RLHF

Source code for 'Understanding impacts of human feedback via influence functions'

Language: Python - Size: 106 KB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 4 - Forks: 0

yzhang511/TimeInf

Time series data contribution via influence functions

Language: Python - Size: 146 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 8 - Forks: 0

hslyu/GIF

Official implementation of "Deeper Understanding of Black-box Predictions via Generalized Influence Functions".

Language: Jupyter Notebook - Size: 5 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 8 - Forks: 0

pomonam/jax-influence

A simple Jax implementation of influence functions.

Language: Python - Size: 39.1 KB - Last synced at: 3 months ago - Pushed at: over 1 year ago - Stars: 16 - Forks: 0

bsharchilev/influence_boosting

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

Language: Python - Size: 16.1 MB - Last synced at: 4 months ago - Pushed at: about 1 year ago - Stars: 67 - Forks: 18

xszheng2020/Classical-LOO

Leave One Out

Language: Jupyter Notebook - Size: 2.62 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 1 - Forks: 0

jjbrophy47/tree_influence

Influence Estimation for Gradient-Boosted Decision Trees

Language: Python - Size: 5.38 MB - Last synced at: 11 months ago - Pushed at: about 1 year ago - Stars: 23 - Forks: 9

RyanWangZf/Influence_Subsampling

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

Language: Python - Size: 11 MB - Last synced at: about 1 year ago - Pushed at: about 4 years ago - Stars: 65 - Forks: 15

ShinKyuY/Understanding_Black_box_Predictions_via_Influence_Functions_tutorial_MNIST

Tiny Tutorial on https://arxiv.org/abs/1703.04730

Language: Jupyter Notebook - Size: 5.6 MB - Last synced at: over 1 year ago - Pushed at: over 5 years ago - Stars: 12 - Forks: 2

ryokamoi/pytorch_influence_functions Fork of nimarb/pytorch_influence_functions

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.

Language: Python - Size: 470 KB - Last synced at: almost 2 years ago - Pushed at: about 5 years ago - Stars: 14 - Forks: 4

feifeiobama/InfluenceCL

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

Language: Python - Size: 420 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 18 - Forks: 0

HKUNLP/ProGen

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

Language: Python - Size: 970 KB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 11 - Forks: 0

MortonWang/geo_IF

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

Language: Python - Size: 8.48 MB - Last synced at: about 2 months ago - Pushed at: about 2 years ago - Stars: 5 - Forks: 0

ICDM-Lab/geo_IF

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

Language: Python - Size: 8.48 MB - Last synced at: over 2 years ago - Pushed at: about 3 years ago - Stars: 3 - Forks: 0

sungyubkim/if_classic

A brief notebook on Influence Function (IF) for classical generative models (e.g., k-NN, KDE, GMM)

Language: Jupyter Notebook - Size: 2.83 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

ajsanjoaquin/pytorch_influence_functions Fork of nimarb/pytorch_influence_functions

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.

Language: Python - Size: 547 KB - Last synced at: over 2 years ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 1

Related Keywords
influence-functions 24 pytorch 5 interpretability 5 machine-learning 4 deep-learning 3 large-language-models 3 data-valuation 3 data-pruning 2 twitter-geolocation 2 explainable-ai 2 explainability 2 pytorch-implementation 2 data-centric-ai 2 interpretable-machine-learning 2 truncated-newton-method 1 black-box-model 1 blackbox 1 influence 1 understanding-neural-networks 1 debugging 1 subsampling 1 noisy-labels 1 newton-cg 1 aaai2020 1 aaai 1 tracin 1 instance-based 1 instance-attribution 1 influential-examples 1 influence-estimation 1 gradient-boosted-trees 1 self-influence-functions 1 numpy 1 kernel-density-estimation 1 kde 1 k-nearest-neighbours 1 k-nearest-neighbors-k-nn 1 k-nearest-neighbors 1 instance-based-interpretability 1 gmm 1 gaussian-mixture-models 1 gnn 1 zero-shot-learning 1 in-context-learning 1 data-generation 1 lifelong-learning 1 influence-function 1 continual-learning 1 transferlab 1 shapley-value 1 robust-machine-learning 1 least-core 1 game-theory 1 data-quality 1 data-cleaning 1 banzhaf-index 1 stable-diffusion 1 diffusion-models 1 ddpm 1 data-attribution 1 attribution 1 propensity-scores 1 inverse-probability-weighting 1 difference-in-differences 1 causal-inference 1 bootstrap-estimator 1 boostin 1 python 1 paper 1 machine-learning-algorithms 1 gradient-boosting 1 catboost 1 unlearning 1 time-series-forecasting 1 time-series-anomaly-detection 1 time-series 1 scalable-oversight 1 rlhf 1 alignment 1 recommender-system 1 data-efficient 1 outlier-detection 1 misclassification 1 fairness-ai 1