amazon-science / long-tailed-ood-detection
Official implementation for "Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition" (ICML'22 Long Presentation)
☆40Updated last year
Related projects ⓘ
Alternatives and complementary repositories for long-tailed-ood-detection
- A list of papers that studies out-of-distribution (OOD) detection and misclassification detection (MisD)☆40Updated last year
- Official code for ICML 2022: Open-Sampling: Exploring Out-of-Distribution Data for Re-balancing Long-tailed Datasets☆14Updated 2 years ago
- PyTorch implementation of our CVPR2023 paper "OpenMix: Exploring Out-of-Distribution samples for Misclassification Detection"☆23Updated last year
- PyTorch implementation of POEM (Out-of-distribution detection with posterior sampling), ICML 2022☆28Updated last year
- PyTorch implementation of CIDER (How to exploit hyperspherical embeddings for out-of-distribution detection), ICLR 2023☆54Updated last year
- ☆16Updated 2 years ago
- Code for TMLR 2023 paper "OpenCon: Open-world Contrastive Learning"☆34Updated last year
- This is an official PyTorch implementation of the ICML 2023 paper AdaNPC and SIGKDD paper DRM.☆81Updated 7 months ago
- This repository is the official implementation of Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regulari…☆21Updated last year
- [ICLR 2022] Open-World Semi-Supervised Learning☆92Updated 2 years ago
- Weakly Supervised Contrastive Learning☆40Updated 3 years ago
- The Official Repository for CVPR2023 Paper "NICO++: Towards Better Benchmarking for Domain Generalization".☆36Updated last year
- [NeurIPS 2022] The official code for our NeurIPS 2022 paper "Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnab…☆42Updated 2 years ago
- ☆25Updated last year
- Twin Contrastive Learning with Noisy Labels (CVPR 2023)☆68Updated last year
- Exploiting Domain-Specific Features to Enhance Domain Generalization (NeurIPS 2021).☆28Updated 2 years ago
- The official code for the publication: "The Close Relationship Between Contrastive Learning and Meta-Learning".☆20Updated 2 years ago
- PyTorch implementation of our ECCV 2022 paper "Rethinking Confidence Calibration for Failure Prediction"☆23Updated last year
- source code for ICLR'23 paper "Non-parametric Outlier Synthesis"☆53Updated last year
- Source code for NeurIPS 2022 paper SoLar☆26Updated 11 months ago
- This codebase is the official implementation of Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization (NeurIPS2…☆93Updated 2 years ago
- Test-Time Adaptation via Conjugate Pseudo-Labels☆38Updated last year
- [ICML 2023] "Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability"☆18Updated last year
- NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"☆38Updated 2 years ago
- [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization☆50Updated 7 months ago
- [AAAI 21] Utilizing meta-learning to correct the noisy labels.☆13Updated 3 years ago
- Code Release for Learning to Adapt to Evolving Domains☆30Updated 3 years ago
- [WACV'23] Mixture Outlier Exposure for Out-of-Distribution Detection in Fine-grained Environments☆25Updated last year
- CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels☆91Updated 2 years ago
- A collection of model transferability estimation methods.☆24Updated last month