gohsyi / PeerLossLinks
Learning with Noisy Labels by adopting a peer prediction loss function.
☆35Updated 5 years ago
Alternatives and similar repositories for PeerLoss
Users that are interested in PeerLoss are comparing it to the libraries listed below
Sorting:
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆89Updated 6 years ago
- Code release for Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers (ICML2019)☆81Updated 6 years ago
- MoPro: Webly Supervised Learning☆88Updated 5 months ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆91Updated 4 years ago
- NeurIPS'18: Masking: A New Perspective of Noisy Supervision☆54Updated 6 years ago
- ICML'19: How does Disagreement Help Generalization against Label Corruption?☆22Updated 6 years ago
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆130Updated 5 years ago
- Chainer Implementation of TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning☆56Updated 5 years ago
- Self-Paced Multi-view Co-training for person re-id experiment☆30Updated 4 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆119Updated 2 years ago
- Meta-Learning based Noise-Tolerant Training☆124Updated 5 years ago
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆127Updated last year
- ☆94Updated 4 years ago
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆34Updated 4 years ago
- Unsupervised Domain Adaptation through Self-Supervision☆79Updated 4 years ago
- Code implementing the experiments described in the paper "On The Power of Curriculum Learning in Training Deep Networks" by Hacohen & Wei…☆114Updated 5 years ago
- Code for 'Joint Optimization Framework for Learning with Noisy Labels'☆38Updated 7 years ago
- Self-supervised Label Augmentation via Input Transformations (ICML 2020)☆106Updated 4 years ago
- Code for ICML2020 "Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation"☆91Updated 4 years ago
- SpotTune: Transfer Learning through Adaptive Fine-tuning☆91Updated 6 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆224Updated 5 years ago
- PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.☆140Updated 6 years ago
- Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…☆53Updated 4 years ago
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 5 years ago
- NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).☆289Updated 3 years ago
- Gold Loss Correction☆88Updated 6 years ago
- Example implementation for the paper: (ICLR Oral) Learning Robust Representations by Projecting Superficial Statistics Out☆27Updated 4 years ago
- ☆130Updated 2 years ago
- Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"☆173Updated 4 years ago
- This is the code of CVPR'20 paper "Distilling Cross-Task Knowledge via Relationship Matching".☆49Updated 4 years ago