youjiangxu / FaMUS
☆29Updated 3 years ago
Alternatives and similar repositories for FaMUS:
Users that are interested in FaMUS are comparing it to the libraries listed below
- Official PyTorch Implementation of "CoSSL: Co-Learning of Representation and Classifier for Imbalanced Semi-Supervised Learning" (CVPR 20…☆52Updated 2 years ago
- Official implementation for: "Multi-Objective Interpolation Training for Robustness to Label Noise"☆39Updated 2 years ago
- [ICML 2021] “ Self-Damaging Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang☆63Updated 3 years ago
- Automatic model evaluation (AutoEval) in CVPR'21&TPAMI'22☆36Updated 2 years ago
- NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"☆39Updated 3 years ago
- (NeurIPS 2020 Workshop on SSL) Official Implementation of "MixCo: Mix-up Contrastive Learning for Visual Representation"☆58Updated 2 years ago
- This is a public repository for:☆38Updated 3 years ago
- ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"☆43Updated 2 years ago
- The official code for the NeurIPS 2021 paper Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels (https://arxiv.org…☆21Updated 3 years ago
- Code for CVPR2020 ‘Training Noise Robust Deep Neural Networks via Meta-Learning’☆20Updated 4 years ago
- Evaluation of semi-supervised learning on challenging datasets☆35Updated 3 years ago
- ☆16Updated 2 years ago
- [ECCV2022] The PyTorch implementation of paper "Equivariance and Invariance Inductive Bias for Learning from Insufficient Data"☆18Updated 2 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
- [ICLR 2021] Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization☆40Updated 3 years ago
- (L2ID@CVPR2021, TNNLS2022) Boosting Co-teaching with Compression Regularization for Label Noise☆47Updated last year
- Pytorch Code for "A Broad Study on the Transferability of Visual Representations with Contrastive Learning" (ICCV 2021)☆36Updated 2 years ago
- Code for NeurIPS 2021 paper "ReAct: Out-of-distribution Detection With Rectified Activations"☆52Updated 2 years ago
- Code for our paper: Samuel and Chechik, "Distributional Robustness Loss for Long-tail Learning"☆29Updated 3 years ago
- ☆59Updated 2 years ago
- Code for "Multi-Task Curriculum Framework for Open-Set Semi-Supervised Learning"☆23Updated 4 years ago
- CVPR2021: Out-of-Distribution Detection Using Union of 1-Dimensional Subspaces☆22Updated 3 years ago
- This code accompanies the paper "Parameter-free Online Test-time Adaptation".☆67Updated 2 years ago
- ☆32Updated 3 years ago
- NeurIPS 2022: Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning☆17Updated last year
- [CVPR 2020] Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective☆24Updated 4 years ago
- [CVPR 2021] MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition☆62Updated 2 years ago
- [ICCV 2021] Released code for Causal Attention for Unbiased Visual Recognition☆75Updated last year
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆36Updated 3 years ago
- Tensorflow Implementation on Paper [AAAI2020]Semi-Supervised Learning under Class Distribution Mismatch☆15Updated 3 years ago