asappresearch / aum
☆80Updated last year
Related projects ⓘ
Alternatives and complementary repositories for aum
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆125Updated 5 years ago
- Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"☆154Updated 4 years ago
- Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018☆178Updated 4 years ago
- Meta-Learning based Noise-Tolerant Training☆123Updated 4 years ago
- Official PyTorch implementation of "Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity" (ICLR'21 Oral)☆104Updated 2 years ago
- Pytorch Implementation of Deep Networks with Stochastic Depth☆63Updated 5 years ago
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆83Updated 5 years ago
- ☆130Updated 2 years ago
- [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels☆134Updated 4 months ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆117Updated last year
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆34Updated 3 years ago
- ☆174Updated 3 months ago
- PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.☆139Updated 5 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆220Updated 4 years ago
- When Does Label Smoothing Help?_pytorch_implementationimp☆124Updated 4 years ago
- Self-supervised Label Augmentation via Input Transformations (ICML 2020)☆104Updated 3 years ago
- A PyTorch converter for SimCLR checkpoints☆106Updated 3 years ago
- REPresentAtion bIas Removal (REPAIR) of datasets☆56Updated last year
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆90Updated 3 years ago
- [CVPR2019]Learning Not to Learn : An adversarial method to train deep neural networks with biased data☆111Updated 4 years ago
- Unofficial PyTorch Reimplementation of AutoAugment and RandAugment.☆36Updated 2 years ago
- Unofficial PyTorch Implementation of Unsupervised Data Augmentation.☆147Updated 4 years ago
- SKD : Self-supervised Knowledge Distillation for Few-shot Learning☆95Updated last year
- "Automatically Discovering and Learning New Visual Categories with Ranking Statistics" by Kai Han, Sylvestre-Alvise Rebuffi, Sebastien Eh…☆224Updated 4 years ago
- Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…☆53Updated 3 years ago
- Zero-Shot Knowledge Distillation in Deep Networks☆64Updated 2 years ago
- Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"☆171Updated 3 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
- Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (Nature Machine Intelligence 2020)☆94Updated 2 years ago
- Compressing Representations for Self-Supervised Learning☆78Updated 3 years ago