pratyushmaini / ssftLinks
[NeurIPS'22] Official Repository for Characterizing Datapoints via Second-Split Forgetting
☆16Updated 2 years ago
Alternatives and similar repositories for ssft
Users that are interested in ssft are comparing it to the libraries listed below
Sorting:
- ☆108Updated last year
- Code for "Just Train Twice: Improving Group Robustness without Training Group Information"☆72Updated last year
- ☆34Updated last year
- ☆23Updated 3 years ago
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated last year
- ☆46Updated 2 years ago
- Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"☆36Updated 2 years ago
- ☆36Updated 4 years ago
- LISA for ICML 2022☆50Updated 2 years ago
- OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift. ICML 2024 and ICLRW-DMLR 2024☆22Updated last year
- Weight-Averaged Sharpness-Aware Minimization (NeurIPS 2022)☆28Updated 2 years ago
- [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”☆48Updated 3 years ago
- Learning from Failure: Training Debiased Classifier from Biased Classifier (NeurIPS 2020)☆91Updated 4 years ago
- ☆34Updated 2 months ago
- Official implementation of paper Gradient Matching for Domain Generalization☆122Updated 3 years ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 3 years ago
- This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC), accepted at ICML 2022.☆22Updated 3 years ago
- [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift☆108Updated 2 years ago
- Official Implementation of Avoiding spurious correlations via logit correction☆17Updated 2 years ago
- This is the code for the paper Bayesian Invariant Risk Minmization of CVPR 2022.☆44Updated 2 years ago
- On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]☆36Updated 4 years ago
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆24Updated 3 years ago
- Code and results accompanying our paper titled RLSbench: Domain Adaptation under Relaxed Label Shift☆34Updated 2 years ago
- Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization☆87Updated 3 years ago
- Code and data for the paper "In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation"☆24Updated 2 years ago
- Understanding Rare Spurious Correlations in Neural Network☆12Updated 3 years ago
- We propose a theoretically motivated method, Adversarial Training with informative Outlier Mining (ATOM), which improves the robustness o…☆57Updated 3 years ago
- Distilling Model Failures as Directions in Latent Space☆47Updated 2 years ago
- [ICLR 2022 official code] Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?☆29Updated 3 years ago
- Code for "Surgical Fine-Tuning Improves Adaptation to Distribution Shifts" published at ICLR 2023☆29Updated 2 years ago