gorkemalgan / corrupting_labels_with_distillationLinks
Code for paper "Label Noise Types and Their Effects on Learning"
☆16Updated 3 years ago
Alternatives and similar repositories for corrupting_labels_with_distillation
Users that are interested in corrupting_labels_with_distillation are comparing it to the libraries listed below
Sorting:
- ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"☆44Updated 3 years ago
- [SafeAI'21] Feature Space Singularity for Out-of-Distribution Detection.☆79Updated 4 years ago
- [NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Z…☆125Updated 3 years ago
- Code for Active Mixup in 2020 CVPR☆23Updated 3 years ago
- Pytorch code for the paper "Deep Active Learning for Joint Classification and Segmentation with Weak Annotator"☆29Updated 3 years ago
- [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels☆141Updated last year
- Code of our method MbLS (Margin-based Label Smoothing) for network calibration. To Appear at CVPR 2022. Paper : https://arxiv.org/abs/211…☆50Updated 3 years ago
- ☆32Updated 4 years ago
- This repository contains some of the latest data augmentation techniques and optimizers for image classification using pytorch and the CI…☆29Updated 4 years ago
- Code for CVPR2021 paper: MOOD: Multi-level Out-of-distribution Detection☆38Updated 2 years ago
- NeurIPS 2020, "A Topological Filter for Learning with Label Noise".☆30Updated 7 months ago
- This is a code repository for paper OODformer: Out-Of-Distribution Detection Transformer☆41Updated 4 years ago
- A list of papers on Active Learning and Uncertainty Estimation for Neural Networks.☆66Updated 5 years ago
- Tiny Imagenet Visual Recognition Challenge☆38Updated 7 years ago
- ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust☆17Updated 4 years ago
- [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…☆44Updated 3 years ago
- [NeurIPS 2021]: Are Transformers More Robust Than CNNs? (Pytorch implementation & checkpoints)☆179Updated 3 years ago
- [ICLR 2021] Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization☆41Updated 4 years ago
- [ICLR 2021 Spotlight Oral] "Undistillable: Making A Nasty Teacher That CANNOT teach students", Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Che…☆82Updated 3 years ago
- [NeurIPS 2021] “Improving Contrastive Learning on Imbalanced Data via Open-World Sampling”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangya…☆29Updated 3 years ago
- Robust Out-of-distribution Detection in Neural Networks☆73Updated 3 years ago
- Official Implementation of Robust Training under Label Noise by Over-parameterization☆64Updated 3 years ago
- The official PyTorch implementation - Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from t…☆83Updated 3 years ago
- Official Pytorch implementation of MixMo framework☆84Updated 4 years ago
- Learning Loss for Active Learning Pytorch Implementation,(reproduction)☆32Updated 5 years ago
- Unofficial pytorch implementation of Fourier Heat Map proposed in 'A Fourier Perspective on Model Robustness in Computer Vision' [Yin+, N…☆75Updated last year
- An implementation of the Residual Flow algorithm for out-of-distribution detection.☆31Updated 3 years ago
- ☆23Updated 6 years ago
- NeurIPS 2022: Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning☆18Updated 2 years ago
- Improving Calibration for Long-Tailed Recognition (CVPR2021)☆152Updated 4 years ago