ildoonet / unsupervised-data-augmentation
Unofficial PyTorch Implementation of Unsupervised Data Augmentation.
☆147Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for unsupervised-data-augmentation
- Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"☆153Updated 4 years ago
- Meta-Learning based Noise-Tolerant Training☆123Updated 4 years ago
- Improving Consistency-Based Semi-Supervised Learning with Weight Averaging☆185Updated 5 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆220Updated 4 years ago
- ☆130Updated last year
- Pytorch implementation of Virtual Adversarial Training☆133Updated 5 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆117Updated last year
- PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.☆139Updated 5 years ago
- Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"☆171Updated 3 years ago
- Virtual Adversarial Training (VAT) implementation for PyTorch☆297Updated 5 years ago
- Pytorch Implementation of the paper MixMatch: A Holistic Approach to Semi-Supervised Learning (https://arxiv.org/pdf/1905.02249.pdf)☆124Updated 5 years ago
- Reproduction of Momentum Contrast for Unsupervised Visual Representation Learning☆120Updated 3 months ago
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆125Updated 5 years ago
- PyTorch code for softmax variants: center loss, cosface loss, large-margin gaussian mixture, COCOLoss, ring loss☆252Updated 6 years ago
- Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018☆178Updated 4 years ago
- PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning☆353Updated 5 years ago
- Code for Paper ''Dual Student: Breaking the Limits of the Teacher in Semi-Supervised Learning'' [ICCV 2019]☆119Updated 4 years ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆90Updated 3 years ago
- Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"☆48Updated 2 years ago
- Code for reproducing ICT (published in Neural Networks 2022, and in IJCAI 2019)☆144Updated 2 years ago
- Reproduce Results for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels" https://arxiv.org/abs/1908.06112☆184Updated 3 years ago
- ☆170Updated 3 years ago
- The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].☆170Updated 2 years ago
- Self-supervised Label Augmentation via Input Transformations (ICML 2020)☆104Updated 3 years ago
- PyTorch implementation of AutoAugment.☆157Updated 4 years ago
- PyTorch implementation of Temporal Ensembling for Semi-Supervised Learning☆109Updated 6 years ago
- Code for Unsupervised Embedding Learning via Invariant and Spreading Instance Feature☆208Updated 5 years ago
- Learning Confidence for Out-of-Distribution Detection in Neural Networks☆267Updated 6 years ago
- Learning What and Where to Transfer (ICML 2019)☆250Updated 4 years ago
- This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.☆235Updated 3 years ago