xdxuyang / ALRDC
☆16Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for ALRDC
- Q. Yao, H. Yang, B. Han, G. Niu, J. Kwok. Searching to Exploit Memorization Effect in Learning from Noisy Labels. ICML 2020☆21Updated 4 years ago
- Code for the article "Confidence Scores Make Instance-dependent Label-noise Learning Possible", ICML'21☆9Updated 2 months ago
- ICML'20: SIGUA: Forgetting May Make Learning with Noisy Labels More Robust☆13Updated 3 years ago
- This repo contains the implementation of the Wasserstein Barycenter Transport proposed in "Wasserstein Barycenter Transport for Acoustic …☆31Updated 2 years ago
- ☆9Updated 11 months ago
- ☆40Updated 4 years ago
- [ICML2020] "Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training" by Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gon…☆67Updated 2 years ago
- Graph Knowledge Distillation☆13Updated 4 years ago
- Implementation of a state-of-art algorithm from the paper “Learning with Noisy Labels” , which is the first one providing “guarantees for…☆22Updated 6 years ago
- ☆30Updated 3 years ago
- [ICASSP 2020] Code release of paper 'Heterogeneous Domain Generalization via Domain Mixup'☆24Updated 4 years ago
- LowFER: Low-rank Bilinear Pooling for Link Prediction (ICML 2020)☆12Updated 2 years ago
- ☆21Updated last year
- Latent Space Virtual Adversarial Training (ECCV 2020)☆17Updated 4 years ago
- [NeurIPS 2021] “Improving Contrastive Learning on Imbalanced Data via Open-World Sampling”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangya…☆28Updated 2 years ago
- ☆16Updated 2 years ago
- Using VAEs to do clustering for classification☆11Updated 7 years ago
- ☆17Updated 2 years ago
- A method based on manifold regularization for training adversarially robust neural networks☆9Updated 4 years ago
- PyTorch implementation of the paper "SuperLoss: A Generic Loss for Robust Curriculum Learning" in NIPS 2020.☆31Updated 3 years ago
- ICML'19: How does Disagreement Help Generalization against Label Corruption?☆21Updated 5 years ago
- Code Release for Learning to Adapt to Evolving Domains☆30Updated 3 years ago
- official PyTorch implementation of paper "Continual Meta-Learning with Bayesian Graph Neural Networks" (AAAI2020)☆61Updated 4 years ago
- The implement of "Learning Disentangled Semantic Representation for Domain Adaptation" (IJCAI 2019)☆19Updated 5 years ago
- NeurIPS 2019 : Learning to Propagate for Graph Meta-Learning☆36Updated 4 years ago
- Learning Representations that Support Robust Transfer of Predictors☆20Updated 3 years ago
- Code for the ICML 2021 paper "Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer"☆11Updated 3 years ago
- Code release for Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning (NeurIPS 2019)☆24Updated 2 years ago
- Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)☆36Updated 3 years ago
- Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning☆43Updated last year