11 papers
Uncertainty-Guided Latent Diagnostic Trajectory Learning for Sequential Clinical Diagnosis
Xuyang Shen, Haoran Liu, Dongjin Song +1
Clinical diagnosis requires sequential evidence acquisition under uncertainty. However, most Large Language Model (LLM) based diagnostic systems assume fully observed patient infor…
Empowering Power Outage Prediction with Spatially Aware Hybrid Graph Neural Networks and Contrastive Learning
Xuyang Shen, Zijie Pan, Diego Cerrai +4
Extreme weather events, such as severe storms, hurricanes, snowstorms, and ice storms, which are exacerbated by climate change, frequently cause widespread power outages. These out…
Early GVHD Prediction in Liver Transplantation via Multi-Modal Deep Learning on Imbalanced EHR Data
Yushan Jiang, Shuteng Niu, Dongjin Song +5
Graft-versus-host disease (GVHD) is a rare but often fatal complication in liver transplantation, with a very high mortality rate. By harnessing multi-modal deep learning methods t…
Towards Interpretable and Trustworthy Time Series Reasoning: A BlueSky Vision
Kanghui Ning, Zijie Pan, Yushan Jiang +3
Time series reasoning is emerging as the next frontier in temporal analysis, aiming to move beyond pattern recognition towards explicit, interpretable, and trustworthy inference. T…
FTSCommDetector: Discovering Behavioral Communities through Temporal Synchronization
Tianyang Luo, Xikun Zhang, Dongjin Song
Why do trillion-dollar tech giants AAPL and MSFT diverge into different response patterns during market disruptions despite identical sector classifications? This paradox reveals a…
Continual Learning to Generalize Forwarding Strategies for Diverse Mobile Wireless Networks
Cheonjin Park, Victoria Manfredi, Xiaolan Zhang +5
Deep reinforcement learning (DRL) has been successfully used to design forwarding strategies for multi-hop mobile wireless networks. While such strategies can be used directly for…