Newbeeer / L_DMI
Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"
☆117Updated last year
Related projects ⓘ
Alternatives and complementary repositories for L_DMI
- Meta-Learning based Noise-Tolerant Training☆123Updated 4 years ago
- Improving Consistency-Based Semi-Supervised Learning with Weight Averaging☆185Updated 5 years ago
- Pytorch implementation of Virtual Adversarial Training☆133Updated 5 years ago
- ICML'19: How does Disagreement Help Generalization against Label Corruption?☆21Updated 5 years ago
- Unofficial PyTorch Implementation of Unsupervised Data Augmentation.☆147Updated 4 years ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆90Updated 3 years 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
- ☆130Updated 2 years ago
- Self-supervised Label Augmentation via Input Transformations (ICML 2020)☆104Updated 3 years ago
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 4 years ago
- DELTA: DEep Learning Transfer using Feature Map with Attention for Convolutional Networks https://arxiv.org/abs/1901.09229☆66Updated 3 years ago
- Reproduction of Momentum Contrast for Unsupervised Visual Representation Learning☆120Updated 3 months ago
- Code release for Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers (ICML2019)☆80Updated 5 years ago
- NeurIPS'18: Masking: A New Perspective of Noisy Supervision☆54Updated 5 years ago
- Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018☆178Updated 4 years ago
- Reimplementation of "Realistic Evaluation of Deep Semi-Supervised Learning Algorithms"☆80Updated 4 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆220Updated 4 years ago
- Max Mahalanobis Training (ICML 2018 + ICLR 2020)☆89Updated 3 years ago
- TRAINING DEEP NEURAL-NETWORKS USING A NOISE ADAPTATION LAYER☆118Updated 7 years ago
- Code for reproducing ICT (published in Neural Networks 2022, and in IJCAI 2019)☆144Updated 2 years ago
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆83Updated 5 years ago
- Deep Metric Transfer for Label Propagation with Limited Annotated Data☆49Updated last year
- Virtual Adversarial Training (VAT) implementation for PyTorch☆297Updated 5 years ago
- Knowledge Distillation with Adversarial Samples Supporting Decision Boundary (AAAI 2019)☆70Updated 5 years ago
- Gold Loss Correction☆86Updated 5 years ago
- The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks☆118Updated 4 years ago
- [TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training☆127Updated 3 years ago
- Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"☆153Updated 4 years ago
- Unsupervised Domain Adaptation through Self-Supervision☆79Updated 3 years ago
- PyTorch implementation of “Negative Margin Matters: Understanding Margin in Few-shot Classification”☆148Updated 3 years ago