VITA-Group / Self-PULinks
[ICML2020] "Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training" by Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gong, Kewei Chen, Zhangyang Wang
☆69Updated 3 years ago
Alternatives and similar repositories for Self-PU
Users that are interested in Self-PU are comparing it to the libraries listed below
Sorting:
- Pytorch implementation of risk estimators for unbiased and non-negative positive-unlabeled learning☆89Updated 10 months ago
- ☆16Updated 4 years ago
- [NeurIPS 2017] [ICML 2019] Code for complementary-label learning☆48Updated last year
- MPVAE: Multivariate Probit Variational AutoEncoder for Multi-Label Classification☆31Updated 9 months ago
- Q. Yao, H. Yang, B. Han, G. Niu, J. Kwok. Searching to Exploit Memorization Effect in Learning from Noisy Labels. ICML 2020☆22Updated 4 years ago
- [AAAI 2021] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning☆139Updated 4 years ago
- ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust☆15Updated 4 years ago
- Code implementing the experiments described in the paper "On The Power of Curriculum Learning in Training Deep Networks" by Hacohen & Wei…☆112Updated 5 years ago
- NeurIPS'20 Paper: "Learning from Positive and Unlabeled Data with Arbitrary Positive Shift"☆17Updated 2 years ago
- This repository is used to record current noisy label paper in mainstream ML and CV conference and journal.☆35Updated 3 years ago
- Code release for Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning (NeurIPS 2019)☆24Updated 3 years ago
- ICML'19 How does Disagreement Help Generalization against Label Corruption?☆85Updated 6 years ago
- CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization☆126Updated last year
- Implementation of Few-shot Domain Adaptation by Causal Mechanism Transfer (ICML 2020)☆42Updated 2 years ago
- Implementation of Multi-View Information Bottleneck☆132Updated 5 years ago
- Virtual Adversarial Training (VAT) for semi-supervised MNIST written in PyTorch: https://arxiv.org/abs/1704.03976☆25Updated 6 years ago
- The implement of "Learning Disentangled Semantic Representation for Domain Adaptation" (IJCAI 2019)☆19Updated 5 years ago
- ☆31Updated 3 years ago
- Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution …☆74Updated 3 years ago
- official PyTorch implementation of paper "Continual Meta-Learning with Bayesian Graph Neural Networks" (AAAI2020)☆63Updated 5 years ago
- ☆40Updated 2 years ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆91Updated 4 years ago
- PyTorch implementation of the paper "SuperLoss: A Generic Loss for Robust Curriculum Learning" in NIPS 2020.☆29Updated 4 years ago
- Implementation of the paper "Understanding anomaly detection with deep invertible networks through hierarchies of distributions and featu…☆42Updated 4 years ago
- A PyTorch implementation of the Variational approach for PU learning☆29Updated 4 years ago
- ICML'19: How does Disagreement Help Generalization against Label Corruption?☆21Updated 6 years ago
- ☆17Updated 2 years ago
- Implementation of the paper "Shapley Explanation Networks"☆88Updated 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 4 years ago
- Official Implementation of Unweighted Data Subsampling via Influence Function - AAAI 2020☆64Updated 4 years ago