92 citations · 105 across the 8 of their papers we have counts for
8 papers
A Noisy-Label-Learning Formulation for Immune Repertoire Classification and Disease-Associated Immune Receptor Sequence Identification
Mingcai Chen, Yu Zhao, Zhonghuang Wang +2
Immune repertoire classification, a typical multiple instance learning (MIL) problem, is a frontier research topic in computational biology that makes transformative contributions…
Reweighted Mixup for Subpopulation Shift
Zongbo Han, Zhipeng Liang, Fan Yang +8
Subpopulation shift exists widely in many real-world applications, which refers to the training and test distributions that contain the same subpopulation groups but with different…
Learning with Noisy Labels over Imbalanced Subpopulations
MingCai Chen, Yu Zhao, Bing He +3
Learning with Noisy Labels (LNL) has attracted significant attention from the research community. Many recent LNL methods rely on the assumption that clean samples tend to have "sm…
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup
Zongbo Han, Zhipeng Liang, Fan Yang +7
Subpopulation shift widely exists in many real-world machine learning applications, referring to the training and test distributions containing the same subpopulation groups but va…
ConCL: Concept Contrastive Learning for Dense Prediction Pre-training in Pathology Images
Jiawei Yang, Hanbo Chen, Yuan Liang +3
Detectingandsegmentingobjectswithinwholeslideimagesis essential in computational pathology workflow. Self-supervised learning (SSL) is appealing to such annotation-heavy tasks. Des…
Seeking Common Ground While Reserving Differences: Multiple Anatomy Collaborative Framework for Undersampled MRI Reconstruction
Jiangpeng Yan, Chenghui Yu, Hanbo Chen +4
Recently, deep neural networks have greatly advanced undersampled Magnetic Resonance Image (MRI) reconstruction, wherein most studies follow the one-anatomy-one-network fashion, i.…
3D Shuffle-Mixer: An Efficient Context-Aware Vision Learner of Transformer-MLP Paradigm for Dense Prediction in Medical Volume
Jianye Pang, Cheng Jiang, Yihao Chen +4
Dense prediction in medical volume provides enriched guidance for clinical analysis. CNN backbones have met bottleneck due to lack of long-range dependencies and global context mod…
Resolution-enhanced parallel coded ptychography for high-throughput optical imaging
Shaowei Jiang, Chengfei Guo, Pengming Song +11
Ptychography is an enabling coherent diffraction imaging technique for both fundamental and applied sciences. Its applications in optical microscopy, however, fall short for its lo…