The official implementation of the ACM MM'21 paper Co-learning: Learning from noisy labels with self-supervision.
☆122May 17, 2022Updated 3 years ago
Alternatives and similar repositories for Co-learning
Users that are interested in Co-learning are comparing it to the libraries listed below
Sorting:
- The official implementation of the ICML'24 paper RFold: Deciphering RNA Secondary Structure Prediction: A Probabilistic K-Rook Matching P…☆89Jul 20, 2024Updated last year
- The official implementation of the CVPR'2022 paper Hyperspherical Consistency Regularization.☆29Jun 22, 2022Updated 3 years ago
- The official implementation of the ICASSP'2023 paper Global-context aware generative protein design.☆27Feb 21, 2023Updated 3 years ago
- ☆11Feb 22, 2023Updated 3 years ago
- ☆14Jan 7, 2023Updated 3 years ago
- The official implementation of the ICLR'23 paper PiFold: Toward effective and efficient protein inverse folding.☆183Jun 17, 2023Updated 2 years ago
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆127Oct 24, 2023Updated 2 years ago
- NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"☆41Nov 29, 2021Updated 4 years ago
- ☆11Sep 27, 2023Updated 2 years ago
- [CVPR'22] Official Implementation of the CVPR 2022 paper "UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learnin…☆62Oct 10, 2024Updated last year
- The official implementation of the ECCV'24 paper MC-CoT: Boosting the Power of Small Multimodal Reasoning Models to Match Larger Models w…☆26May 19, 2024Updated last year
- ICLR 2021: Noise against noise: stochastic label noise helps combat inherent label noise☆15May 1, 2021Updated 4 years ago
- The official implementation of the CVPR'22 paper SimVP: Simpler Yet Better Video Prediction.☆288Feb 21, 2023Updated 3 years ago
- NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels☆519Aug 19, 2021Updated 4 years ago
- A curated list of resources for Learning with Noisy Labels☆2,722May 3, 2025Updated 10 months ago
- The official implementation of the NeurIPS'23 paper ProteinInvBench: Benchmarking Protein Design on Diverse Tasks, Models, and Metrics☆200Sep 18, 2024Updated last year
- A Survey☆572Feb 13, 2023Updated 3 years ago
- some methods about automated thermography defects detection☆21Nov 16, 2023Updated 2 years ago
- Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning☆575Sep 14, 2020Updated 5 years ago
- density growing clustering☆10Dec 2, 2021Updated 4 years ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆91Dec 10, 2020Updated 5 years ago
- This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.☆236Sep 20, 2021Updated 4 years ago
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆129Nov 12, 2019Updated 6 years ago
- ☆13May 25, 2022Updated 3 years ago
- CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels☆95Mar 28, 2022Updated 3 years ago
- ICME2022 Special Session “Beyond Accuracy: Responsible, Responsive, and Robust Multimedia Retrieval ”☆12Jun 3, 2024Updated last year
- Benchmark for federated noisy label learning☆25Aug 31, 2024Updated last year
- VQ-GAN for Various Data Modality based on Taming Transformers for High-Resolution Image Synthesis☆28Apr 15, 2023Updated 2 years ago
- [ICML 2024] VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling☆10Sep 22, 2024Updated last year
- Learning with Noisy Labels by adopting a peer prediction loss function.☆35Mar 3, 2020Updated 6 years ago
- ☆15Oct 5, 2020Updated 5 years ago
- Code for TNNLS paper "Homophily-Enhanced Self-supervision for Graph Structure Learning: Insights and Directions"☆15Feb 27, 2024Updated 2 years ago
- 基于WebCollector的新浪微博爬虫及相关登录工具,如新浪微博Cookie获取☆14Nov 21, 2018Updated 7 years ago
- Pytorch implementations of Co-teaching for noisy label learning☆13Jun 28, 2022Updated 3 years ago
- ☆12Feb 19, 2023Updated 3 years ago
- NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).☆292Dec 14, 2021Updated 4 years ago
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆89Jun 30, 2019Updated 6 years ago
- [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels☆141Jul 5, 2024Updated last year
- [AAAI 21] Utilizing meta-learning to correct the noisy labels.☆15Apr 26, 2021Updated 4 years ago