Newbeeer / L_DMILinks
Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"
☆119Updated 2 years ago
Alternatives and similar repositories for L_DMI
Users that are interested in L_DMI are comparing it to the libraries listed below
Sorting:
- Meta-Learning based Noise-Tolerant Training☆123Updated 5 years ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆91Updated 5 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆225Updated 5 years ago
- The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].☆175Updated 4 years ago
- Improving Consistency-Based Semi-Supervised Learning with Weight Averaging☆188Updated 6 years ago
- Unofficial PyTorch Implementation of Unsupervised Data Augmentation.☆148Updated 5 years ago
- Reproduction of Momentum Contrast for Unsupervised Visual Representation Learning☆120Updated last year
- Code release for Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers (ICML2019)☆81Updated 6 years ago
- ☆131Updated 3 years ago
- Learning What and Where to Transfer (ICML 2019)☆250Updated 5 years ago
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 5 years ago
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆90Updated 6 years ago
- Tensorflow code for ICML 2019 paper: LGM-Net: Learning to Generate Matching Networks for Few-Shot Learning☆84Updated 5 years ago
- NeurIPS'18: Masking: A New Perspective of Noisy Supervision☆55Updated 7 years ago
- Pytorch implementation of Virtual Adversarial Training☆134Updated 6 years ago
- Unofficial pytorch implementation of Born-Again Neural Networks.☆56Updated 4 years ago
- SpotTune: Transfer Learning through Adaptive Fine-tuning☆91Updated 6 years ago
- Full implementation of the paper "Rethinking Softmax with Cross-Entropy: Neural Network Classifier as Mutual Information Estimator".☆101Updated 5 years ago
- Tensorflow codes for ICML2018, Learning Semantic Representations for Unsupervised Domain Adaptation☆110Updated 7 years ago
- Code for ICLR19 paper: Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning.☆244Updated 6 years ago
- Deep Metric Transfer for Label Propagation with Limited Annotated Data☆50Updated 2 years ago
- PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.☆140Updated 6 years ago
- Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"☆155Updated 5 years ago
- Official Pytorch Implementation for ICML'19 paper: Unsupervised Deep Learning by Neighbourhood Discovery☆156Updated 6 years ago
- Code for reproducing ICT (published in Neural Networks 2022, and in IJCAI 2019)☆148Updated 3 years ago
- ICML'19: How does Disagreement Help Generalization against Label Corruption?☆22Updated 6 years ago
- PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning☆354Updated 6 years ago
- ☆95Updated 5 years ago
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆127Updated 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