acmi-lab / RLSbenchLinks
Code and results accompanying our paper titled RLSbench: Domain Adaptation under Relaxed Label Shift
☆35Updated 2 years ago
Alternatives and similar repositories for RLSbench
Users that are interested in RLSbench are comparing it to the libraries listed below
Sorting:
- LISA for ICML 2022☆50Updated 2 years ago
- ☆46Updated 2 years ago
- DiWA: Diverse Weight Averaging for Out-of-Distribution Generalization☆31Updated 2 years ago
- Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"☆36Updated 2 years ago
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆24Updated 3 years ago
- ☆31Updated 3 years ago
- ☆12Updated 2 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆42Updated last year
- ☆108Updated last year
- ☆36Updated 4 years ago
- Code for "Just Train Twice: Improving Group Robustness without Training Group Information"☆72Updated last year
- ☆44Updated 4 months ago
- Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization☆87Updated 3 years ago
- This repository is the official implementation of Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regulari…☆21Updated 2 years ago
- ☆23Updated 3 years ago
- Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)☆67Updated 2 years ago
- ☆57Updated 3 years ago
- Learning Representations that Support Robust Transfer of Predictors☆20Updated 3 years ago
- ☆34Updated 2 months ago
- [NeurIPS'22] Official Repository for Characterizing Datapoints via Second-Split Forgetting☆16Updated 2 years ago
- ☆18Updated 3 years ago
- Deep Learning & Information Bottleneck☆61Updated 2 years ago
- ☆36Updated 2 years ago
- ☆27Updated last year
- C-Mixup for NeurIPS 2022☆71Updated last year
- Recycling diverse models☆45Updated 2 years ago
- Codebase for the paper titled "Continual learning with local module selection"☆25Updated 3 years ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 3 years ago
- Repository for the NeurIPS 2023 paper "Beyond Confidence: Reliable Models Should Also Consider Atypicality"☆13Updated last year
- Distilling Model Failures as Directions in Latent Space☆47Updated 2 years ago