ryokamoi / 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.
☆16Updated 4 years ago
Alternatives and similar repositories for pytorch_influence_functions
Users that are interested in pytorch_influence_functions are comparing it to the libraries listed below
Sorting:
- ☆14Updated 5 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆50Updated 3 years ago
- A simple PyTorch implementation of influence functions.☆85Updated 10 months ago
- Code for "Just Train Twice: Improving Group Robustness without Training Group Information"☆71Updated 11 months ago
- ☆50Updated 2 years ago
- Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"☆18Updated 2 years ago
- Influence Analysis and Estimation - Survey, Papers, and Taxonomy☆77Updated last year
- ☆9Updated last year
- ☆22Updated 5 years ago
- Understanding Rare Spurious Correlations in Neural Network☆12Updated 2 years ago
- [ICLR 2023, Spotlight] Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning☆30Updated last year
- [NeurIPS 2020] code for "Boundary thickness and robustness in learning models"☆19Updated 4 years ago
- ☆17Updated 3 years ago
- On the effectiveness of adversarial training against common corruptions [UAI 2022]☆30Updated 3 years ago
- This is the code for the paper Bayesian Invariant Risk Minmization of CVPR 2022.☆44Updated last year
- Certified Removal from Machine Learning Models☆65Updated 3 years ago
- ☆53Updated last year
- Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"☆34Updated 5 years ago
- [ICLR 2022 official code] Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?☆29Updated 3 years ago
- ☆62Updated 3 years ago
- An Investigation of Why Overparameterization Exacerbates Spurious Correlations☆31Updated 4 years ago
- Code repository for the paper "Invariant and Transportable Representations for Anti-Causal Domain Shifts"☆16Updated 2 years ago
- ☆22Updated 6 years ago
- Learning from Failure: Training Debiased Classifier from Biased Classifier (NeurIPS 2020)☆91Updated 4 years ago
- ☆34Updated last year
- ☆9Updated 4 years ago
- ☆30Updated 3 years ago
- ☆12Updated last year
- Code for the ICLR 2021 Paper "In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness"☆12Updated 3 years ago
- PyTorch code for the Neurips 2021 paper: Fairness via Representation Neutralization☆10Updated 3 years ago