Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)
☆38Feb 24, 2021Updated 5 years ago
Alternatives and similar repositories for cores
Users that are interested in cores are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- A Second-Order Approach to Learning with Instance-Dependent Label Noise (CVPR'21 oral)☆42Nov 24, 2022Updated 3 years ago
- Learning from noisy labels via regularization between representations☆11Feb 28, 2023Updated 3 years ago
- [ICML'2022] Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network☆21Jul 19, 2022Updated 4 years ago
- ☆76May 17, 2023Updated 3 years ago
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆35Feb 24, 2021Updated 5 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise☆35Jun 9, 2021Updated 5 years ago
- ☆26May 17, 2023Updated 3 years ago
- PyTorch implementation of "Contrast to Divide: self-supervised pre-training for learning with noisy labels"☆69Mar 30, 2021Updated 5 years ago
- ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"☆46Oct 29, 2022Updated 4 years ago
- Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels☆302May 22, 2023Updated 3 years ago
- ☆14Jan 7, 2023Updated 3 years ago
- ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels☆77Jun 15, 2021Updated 5 years ago
- The source code and models for our paper PNP: Robust Learning from Noisy Labels by Probabilistic Noise Prediction☆14Jan 30, 2023Updated 3 years ago
- PyTorch implementation for our paper EvidentialMix: Learning with Combined Open-set and Closed-set Noisy Labels☆28Nov 18, 2020Updated 5 years ago
- Proton VPN Special Offer - Get 70% off • AdSpecial partner offer. Trusted by over 100 million users worldwide. Tested, Approved and Recommended by Experts.
- [NeurIPS2024] $\epsilon$-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise☆10Oct 5, 2026Updated 3 weeks ago
- This is the official repo for our CVPR22 paper: Scalable Penalized Regression for Noise Detection in Learning With Noisy Labels.☆20Mar 21, 2024Updated 2 years ago
- Official Implementation of IJCAI-ECAI-2022 1st Learning and Mining with Noisy Labels Challenge Runner-up "Noise-Robust Bidirectional Lear…☆12Oct 10, 2024Updated 2 years ago
- A PyTorch-based library for On Learning Contrastive Representations for Learning With Noisy Labels (CVPR'22)☆43Sep 8, 2022Updated 4 years ago
- [IJCAI 2023] ProMix: Combating Label Noise via Maximizing Clean Sample Utility☆80May 10, 2024Updated 2 years ago
- Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning☆576Sep 14, 2020Updated 6 years ago
- Benchmark for federated noisy label learning☆29Aug 31, 2024Updated 2 years ago
- ☆61Apr 17, 2024Updated 2 years ago
- [Under Progress] Code & Data for the AAAI 2020 Paper "Likelihood Ratios and Generative Classifiers For Unsupervised OOD Detection In Task…☆10Jul 25, 2024Updated 2 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels☆95Mar 28, 2022Updated 4 years ago
- NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"☆41Nov 29, 2021Updated 4 years ago
- [CVPR2023] DISC: Learning from Noisy Labels via Dynamic Instance-Specific Selection and Correction☆58Aug 23, 2026Updated 2 months ago
- implement of paper 'Probabilistic End-to-end Noise Correction for Learning with Noisy Labels'☆16Jul 18, 2019Updated 7 years ago
- A curated (most recent) list of resources for Learning with Noisy Labels☆736Oct 18, 2024Updated 2 years ago
- AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images☆13May 14, 2018Updated 8 years ago
- [ICLR 2021] Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization☆42May 2, 2021Updated 5 years ago
- Official Implementation of Robust Training under Label Noise by Over-parameterization☆66Sep 15, 2022Updated 4 years ago
- Normalized Wasserstein for Mixture Distributions☆11Mar 24, 2023Updated 3 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Official Implementation of AAAI'24 paper "Dirichlet-Based Prediction Calibration for Learning with Noisy Labels"☆13Sep 22, 2024Updated 2 years ago
- ☆29Jun 4, 2023Updated 3 years ago
- [CVPR'22] Official Implementation of the CVPR 2022 paper "UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learnin…☆63Oct 10, 2024Updated 2 years ago
- Code for CVPR2021 paper: MOOD: Multi-level Out-of-distribution Detection☆38Sep 4, 2023Updated 3 years ago
- ECCV22 "Improving Covariance Conditioning of the SVD Meta-layer by Orthogonality" and T-PAMI extension☆12Dec 13, 2022Updated 3 years ago
- ☆14Mar 1, 2023Updated 3 years ago
- Source code for the NeurIPS 2023 paper: "CSOT: Curriculum and Structure-Aware Optimal Transport for Learning with Noisy Labels"☆19Dec 11, 2023Updated 2 years ago