erosenfeld / disagree_discrep
Provably (and non-vacuously) bounding test error of deep neural networks under distribution shift with unlabeled test data.
☆9Updated 11 months ago
Alternatives and similar repositories for disagree_discrep:
Users that are interested in disagree_discrep are comparing it to the libraries listed below
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated last year
- Preprint: Asymmetry in Low-Rank Adapters of Foundation Models☆34Updated 11 months ago
- Code for the paper "Data Feedback Loops: Model-driven Amplification of Dataset Biases"☆15Updated 2 years ago
- Code and results accompanying our paper titled RLSbench: Domain Adaptation under Relaxed Label Shift☆34Updated last year
- Code for the paper "The Journey, Not the Destination: How Data Guides Diffusion Models"☆21Updated last year
- Distilling Model Failures as Directions in Latent Space☆46Updated 2 years ago
- DiWA: Diverse Weight Averaging for Out-of-Distribution Generalization☆29Updated 2 years ago
- ☆17Updated 2 years ago
- Spurious Features Everywhere - Large-Scale Detection of Harmful Spurious Features in ImageNet☆30Updated last year
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆23Updated 3 years ago
- ☆28Updated 7 months ago
- ☆17Updated 7 months ago
- Post-processing for fair classification☆13Updated last month
- ☆44Updated 2 years ago
- Source code of "What can linearized neural networks actually say about generalization?☆20Updated 3 years ago
- Code for NeurIPS'23 paper "A Bayesian Approach To Analysing Training Data Attribution In Deep Learning"☆15Updated last year
- Official repo of Progressive Data Expansion: data, code and evaluation☆28Updated last year
- ☆13Updated 2 years ago
- ☆39Updated 2 years ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆26Updated 3 years ago
- ☆28Updated last year
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 2 years ago
- Code for paper "Out-of-Domain Robustness via Targeted Augmentations"☆13Updated last year
- ☆21Updated 4 months ago
- Energy-Based Models for Continual Learning Official Repository (PyTorch)☆40Updated 2 years ago
- ☆15Updated last year
- ☆30Updated 2 months ago
- Understanding Rare Spurious Correlations in Neural Network☆12Updated 2 years ago
- ☆12Updated 11 months ago
- A simple and efficient baseline for data attribution☆11Updated last year