chenpf1025 / SLNLinks
ICLR 2021: Noise against noise: stochastic label noise helps combat inherent label noise
☆14Updated 4 years ago
Alternatives and similar repositories for SLN
Users that are interested in SLN are comparing it to the libraries listed below
Sorting:
- ☆28Updated 3 years ago
- [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…☆44Updated 3 years ago
- Pytorch implementation for ICLR 2021 paper - MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering☆51Updated 4 years ago
- ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust☆15Updated 4 years ago
- [NeurIPS 2021] “Improving Contrastive Learning on Imbalanced Data via Open-World Sampling”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangya…☆28Updated 3 years ago
- ☆29Updated 2 years ago
- Paper and Code for "Curriculum Learning by Optimizing Learning Dynamics" (AISTATS 2021)☆19Updated 3 years ago
- Implementation for Jacobian Adversarially Regularized Networks for Robustness (ICLR 2020)☆22Updated 5 years ago
- Learning Representations that Support Robust Transfer of Predictors☆20Updated 3 years ago
- Example implementation for the paper: (ICLR Oral) Learning Robust Representations by Projecting Superficial Statistics Out☆27Updated 4 years ago
- Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxi…☆68Updated 3 years ago
- PyTorch implementation of the paper "SuperLoss: A Generic Loss for Robust Curriculum Learning" in NIPS 2020.☆29Updated 4 years ago
- The official code for the NeurIPS 2021 paper Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels (https://arxiv.org…☆22Updated 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
- ☆42Updated 4 years ago
- Implementation for What it Thinks is Important is Important: Robustness Transfers through Input Gradients (CVPR 2020 Oral)☆16Updated 2 years ago
- Codes for our ICLR2020 paper: Knowledge Consistency between Neural Networks and Beyond☆16Updated 5 years ago
- 90%+ with 40 labels. please see the readme for details.☆37Updated 4 years ago
- Code for paper "Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning", Ren et al., NeurIPS'20☆25Updated 4 years ago
- ☆10Updated 5 years ago
- [ECCV2022] The PyTorch implementation of paper "Equivariance and Invariance Inductive Bias for Learning from Insufficient Data"☆19Updated 2 years ago
- [ICASSP 2020] Code release of paper 'Heterogeneous Domain Generalization via Domain Mixup'☆26Updated 4 years ago
- pytorch implementation of manifold-mixup☆22Updated 2 years ago
- Q. Yao, H. Yang, B. Han, G. Niu, J. Kwok. Searching to Exploit Memorization Effect in Learning from Noisy Labels. ICML 2020☆22Updated 4 years ago
- [NeurIPS 2020] “ Robust Pre-Training by Adversarial Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang☆114Updated 3 years ago
- [CVPR 2020] Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning☆85Updated 3 years ago
- ICLR 2021, Fair Mixup: Fairness via Interpolation☆56Updated 3 years ago
- [ICML 2021] “ Self-Damaging Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang☆63Updated 3 years ago
- This is a code repository for paper OODformer: Out-Of-Distribution Detection Transformer☆40Updated 3 years ago
- ICLR 2022 Paper submission trend analysis from https://openreview.net/group?id=ICLR.cc/2022/Conference☆84Updated 2 years ago