JasonZhang156 / awesome-mixed-sample-data-augmentationLinks
A collection of awesome things about mixed sample data augmentation
☆132Updated 5 years ago
Alternatives and similar repositories for awesome-mixed-sample-data-augmentation
Users that are interested in awesome-mixed-sample-data-augmentation are comparing it to the libraries listed below
Sorting:
- Reproduce Results for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels" https://arxiv.org/abs/1908.06112☆190Updated 4 years ago
- Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"☆171Updated 4 years ago
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆126Updated 2 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
- [AAAI 2021] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning☆139Updated 4 years ago
- [CVPR 2021] Adaptive Consistency Regularization for Semi-Supervised Transfer Learning☆106Updated 4 years ago
- "In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning" by Mamshad Nayeem Riz…☆236Updated 2 years ago
- When Does Label Smoothing Help?_pytorch_implementationimp☆126Updated 5 years ago
- [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels☆141Updated last year
- Regularizing Class-wise Predictions via Self-knowledge Distillation (CVPR 2020)☆109Updated 5 years ago
- PyTorch implementation of consistency regularization methods for semi-supervised learning☆79Updated 5 years ago
- Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"☆155Updated 5 years ago
- PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.☆140Updated 6 years ago
- [NeurIPS 2020] Released code for Interventional Few-Shot Learning☆169Updated 4 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆224Updated 5 years ago
- This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.☆236Updated 4 years ago
- PseudoLabel 2013, VAT, PI model, Tempens, MeanTeacher, ICT, MixMatch, FixMatch☆452Updated 2 years ago
- Implementation of Adversarial Domain Adaptation with Domain Mixup (AAAI 2020 Oral).☆163Updated 5 years ago
- The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].☆176Updated 3 years ago
- awesome few shot / meta learning papers☆53Updated 4 years ago
- ☆94Updated 5 years ago
- Meta-Learning based Noise-Tolerant Training☆123Updated 5 years ago
- [ECCV2020] Knowledge Distillation Meets Self-Supervision☆238Updated 2 years ago
- [ICLR2021 Oral] Free Lunch for Few-Shot Learning: Distribution Calibration☆474Updated 4 years ago
- [CVPR 2021] Released code for Counterfactual Zero-Shot and Open-Set Visual Recognition☆164Updated 4 years ago
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆90Updated 6 years ago
- Pytorch Implementation of Domain Generalization Using a Mixture of Multiple Latent Domains☆105Updated 4 years ago
- NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).☆290Updated 3 years ago
- PyTorch implementation of Temporal Ensembling for Semi-Supervised Learning☆111Updated 7 years ago
- Pytorch implementation for Deep Self-Learning From Noisy Labels☆33Updated 5 years ago