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cs.LG2026

A Clinical Point Cloud Paradigm for In-Hospital Mortality Prediction from Multi-Level Incomplete Multimodal EHRs

Bohao Li, Tao Zou, Junchen Ye +2

Deep learning-based modeling of multimodal Electronic Health Records (EHRs) has become an important approach for clinical diagnosis and risk prediction. However, due to diverse cli…

cs.LG2026

Incident-Guided Spatiotemporal Traffic Forecasting

Lixiang Fan, Bohao Li, Tao Zou +2

Recent years have witnessed the rapid development of deep-learning-based, graph-neural-network-based forecasting methods for modern intelligent transportation systems. However, mos…

cs.LG2025

Global-Lens Transformers: Adaptive Token Mixing for Dynamic Link Prediction

Tao Zou, Chengfeng Wu, Tianxi Liao +2

Dynamic graph learning plays a pivotal role in modeling evolving relationships over time, especially for temporal link prediction tasks in domains such as traffic systems, social n…

cs.LG2024

Dynamic Graph Representation Learning for Passenger Behavior Prediction

Mingxuan Xie, Tao Zou, Junchen Ye +2

Passenger behavior prediction aims to track passenger travel patterns through historical boarding and alighting data, enabling the analysis of urban station passenger flow and time…

cs.LG2024

Co-Neighbor Encoding Schema: A Light-cost Structure Encoding Method for Dynamic Link Prediction

Ke Cheng, Linzhi Peng, Junchen Ye +2

Structure encoding has proven to be the key feature to distinguishing links in a graph. However, Structure encoding in the temporal graph keeps changing as the graph evolves, repea…

cs.LG2024

DyGKT: Dynamic Graph Learning for Knowledge Tracing

Ke Cheng, Linzhi Peng, Pengyang Wang +3

Knowledge Tracing aims to assess student learning states by predicting their performance in answering questions. Different from the existing research which utilizes fixed-length le…