152 citations · 423 across the 28 of their papers we have counts for
9 papers · 1 filter
Mixed Transformer U-Net For Medical Image Segmentation
Hongyi Wang, Shiao Xie, Lanfen Lin +4
Though U-Net has achieved tremendous success in medical image segmentation tasks, it lacks the ability to explicitly model long-range dependencies. Therefore, Vision Transformers h…
Collaborative Semantic Aggregation and Calibration for Federated Domain Generalization
Junkun Yuan, Xu Ma, Defang Chen +3
Domain generalization (DG) aims to learn from multiple known source domains a model that can generalize well to unknown target domains. The existing DG methods usually exploit the…
Instrumental Variable-Driven Domain Generalization with Unobserved Confounders
Junkun Yuan, Xu Ma, Ruoxuan Xiong +5
Domain generalization (DG) aims to learn from multiple source domains a model that can generalize well on unseen target domains. Existing DG methods mainly learn the representation…
Domain-Specific Bias Filtering for Single Labeled Domain Generalization
Junkun Yuan, Xu Ma, Defang Chen +3
Conventional Domain Generalization (CDG) utilizes multiple labeled source datasets to train a generalizable model for unseen target domains. However, due to expensive annotation co…
Multi-phase Liver Tumor Segmentation with Spatial Aggregation and Uncertain Region Inpainting
Yue Zhang, Chengtao Peng, Liying Peng +8
Multi-phase computed tomography (CT) images provide crucial complementary information for accurate liver tumor segmentation (LiTS). State-of-the-art multi-phase LiTS methods usuall…
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition
Junkun Yuan, Anpeng Wu, Kun Kuang +4
Instrumental variables (IVs), sources of treatment randomization that are conditionally independent of the outcome, play an important role in causal inference with unobserved confo…