MadryLab / pretraining-distribution-shift-robustnessLinks
☆14Updated last year
Alternatives and similar repositories for pretraining-distribution-shift-robustness
Users that are interested in pretraining-distribution-shift-robustness are comparing it to the libraries listed below
Sorting:
- Code for the paper "The Journey, Not the Destination: How Data Guides Diffusion Models"☆22Updated last year
- Code for the paper "Evading Black-box Classifiers Without Breaking Eggs" [SaTML 2024]☆20Updated last year
- Understanding Rare Spurious Correlations in Neural Network☆12Updated 3 years ago
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated last year
- ☆16Updated last year
- ☆34Updated last year
- Distilling Model Failures as Directions in Latent Space☆47Updated 2 years ago
- Official repo for the paper "Make Some Noise: Reliable and Efficient Single-Step Adversarial Training" (https://arxiv.org/abs/2202.01181)☆25Updated 2 years ago
- ☆55Updated 4 years ago
- Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation☆45Updated 2 years ago
- Repository for Knowledge Enhanced Machine Learning Pipeline (KEMLP)☆10Updated 4 years ago
- ☆22Updated 10 months ago
- Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"☆19Updated 2 years ago
- ☆45Updated 2 years ago
- Code for the paper "Efficient Dataset Distillation using Random Feature Approximation"☆37Updated 2 years ago
- What do we learn from inverting CLIP models?☆54Updated last year
- ☆18Updated 2 years ago
- Host CIFAR-10.2 Data Set☆13Updated 3 years ago
- ☆28Updated 2 years ago
- A simple and efficient baseline for data attribution☆11Updated last year
- [NeurIPS'22] Official Repository for Characterizing Datapoints via Second-Split Forgetting☆15Updated last year
- Post-processing for fair classification☆13Updated last month
- kyleliang919 / Uncovering-the-Connections-BetweenAdversarial-Transferability-and-Knowledge-Transferabilitycode for ICML 2021 paper in which we explore the relationship between adversarial transferability and knowledge transferability.☆17Updated 2 years ago
- ☆30Updated 10 months ago
- Do input gradients highlight discriminative features? [NeurIPS 2021] (https://arxiv.org/abs/2102.12781)☆13Updated 2 years ago
- Code and results accompanying our paper titled RLSbench: Domain Adaptation under Relaxed Label Shift☆34Updated last year
- [ICML 2023] "Robust Weight Signatures: Gaining Robustness as Easy as Patching Weights?" by Ruisi Cai, Zhenyu Zhang, Zhangyang Wang☆16Updated 2 years ago
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆24Updated 3 years ago
- This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC), accepted at ICML 2022.☆21Updated 2 years ago
- Code for NeurIPS'23 paper "A Bayesian Approach To Analysing Training Data Attribution In Deep Learning"☆17Updated last year