pingqingsheng / LRTLinks
☆24Updated 3 years ago
Alternatives and similar repositories for LRT
Users that are interested in LRT are comparing it to the libraries listed below
Sorting:
- PyTorch implementation of the paper "SuperLoss: A Generic Loss for Robust Curriculum Learning" in NIPS 2020.☆29Updated 4 years ago
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆127Updated 2 years ago
- ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"☆45Updated 3 years ago
- Multi-Label Learning from Single Positive Labels - CVPR 2021☆97Updated 2 years ago
- [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels☆141Updated last year
- PyTorch implementations of "Unsupervised Semantic Aggregation and Deformable Template Matching for Semi-Supervised Learning" (NeurIPS2020…☆31Updated 5 years ago
- Q. Yao, H. Yang, B. Han, G. Niu, J. Kwok. Searching to Exploit Memorization Effect in Learning from Noisy Labels. ICML 2020☆23Updated 5 years ago
- NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"☆40Updated 4 years ago
- paper "O2U-Net: A Simple Noisy Label Detection Approach for Deep Neural Networks" code☆78Updated 3 years ago
- [AAAI 2021] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning☆139Updated 5 years ago
- ☆28Updated 4 years ago
- Code of our method MbLS (Margin-based Label Smoothing) for network calibration. To Appear at CVPR 2022. Paper : https://arxiv.org/abs/211…☆50Updated 3 years ago
- ☆32Updated 4 years ago
- [NeurIPS 2021] “Improving Contrastive Learning on Imbalanced Data via Open-World Sampling”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangya…☆29Updated 4 years ago
- [ICLR 2021] Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization☆42Updated 4 years ago
- Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"☆171Updated 4 years ago
- Code release for Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning (NeurIPS 2019)☆24Updated 4 years ago
- MSc group project: Reproduction of 'Multi-Task Learning using Uncertainty to Weigh Losses for Scene Geometry and Semantics'; A. Kendall, …☆91Updated 6 years ago
- CrossNorm and SelfNorm for Generalization under Distribution Shifts, ICCV 2021☆128Updated 4 years ago
- Code for "Learning From Multiple Experts: Self-paced Knowledge Distillation for Long-tailed Classification", ECCV 2020 Spotlight☆38Updated 4 years ago
- Repo for CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning☆101Updated last year
- IJCAI 2021, "Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation"☆42Updated 2 years ago
- Learning with Noisy Labels, Label Noise, ICML 2021☆46Updated 2 years ago
- Official code for ICML 2022: Mitigating Neural Network Overconfidence with Logit Normalization☆154Updated 3 years ago
- Ranking-based-Instance-Selection☆33Updated 4 years ago
- PyTorch code for the paper "CrossTransformers: spatially-aware few-shot transfer"☆25Updated 5 years ago
- Large Loss Matters in Weakly Supervised Multi-Label Classification - CVPR2022☆46Updated 2 years ago
- PyTorch implementation of consistency regularization methods for semi-supervised learning☆79Updated 5 years ago
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆90Updated 6 years ago
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆130Updated 6 years ago