UCSC-REAL / cores
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)
☆36Updated 3 years ago
Alternatives and similar repositories for cores:
Users that are interested in cores are comparing it to the libraries listed below
- NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"☆39Updated 3 years ago
- A pytorch implementation for "Neighborhood Collective Estimation for Noisy Label Identification and Correction", which is accepted by ECC…☆25Updated last year
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆34Updated 3 years ago
- ☆30Updated 2 years ago
- ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels☆75Updated 3 years ago
- ☆14Updated 2 years ago
- ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"☆43Updated 2 years ago
- [NeurIPS 2017] [ICML 2019] Code for complementary-label learning☆46Updated last year
- [ICLR 2021] Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization☆40Updated 3 years ago
- [AAAI 21] Utilizing meta-learning to correct the noisy labels.☆13Updated 3 years ago
- CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels☆90Updated 2 years ago
- Meta Label Correction for Noisy Label Learning☆84Updated 2 years ago
- ☆17Updated 2 years ago
- Code for "Multi-Task Curriculum Framework for Open-Set Semi-Supervised Learning"☆23Updated 4 years ago
- Official Implementation of Robust Training under Label Noise by Over-parameterization☆63Updated 2 years ago
- Source code for NeurIPS 2022 paper SoLar☆27Updated last year
- Official implementation of "Open-set Label Noise Can Improve Robustness Against Inherent Label Noise" (NeurIPS 2021)☆19Updated 2 years ago
- Learning with Noisy Labels by adopting a peer prediction loss function.☆35Updated 4 years ago
- Code for CVPR2020 ‘Training Noise Robust Deep Neural Networks via Meta-Learning’☆20Updated 4 years ago
- [ICML'2022] Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network☆19Updated 2 years ago
- AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise☆35Updated 3 years ago
- Official implementation for: "Multi-Objective Interpolation Training for Robustness to Label Noise"☆39Updated 2 years ago
- This is the official repo for our CVPR22 paper: Scalable Penalized Regression for Noise Detection in Learning With Noisy Labels.☆18Updated 11 months ago
- Code release for Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning (NeurIPS 2019)☆24Updated 3 years ago
- ☆44Updated 3 years ago
- Instance-Dependent Partial Label Learning（NIPS'21）；Variational Label Enhancement for Instance-Dependent Partial Label Learning（TPAMI）☆24Updated 5 months ago
- [CVPR'22] Official Implementation of the CVPR 2022 paper "UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learnin…☆61Updated 4 months ago
- Learning from noisy labels via regularization between representations☆11Updated last year
- [NeurIPS'20] Semi-Supervised Partial Label Learning via Confidence-Rated Margin Maximization☆19Updated 2 years ago
- [CVPR 2020] Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective☆24Updated 4 years ago