14 citations · 39 across the 19 of their papers we have counts for
7 papers · 1 filter
Temporal-spatial Correlation Attention Network for Clinical Data Analysis in Intensive Care Unit
Weizhi Nie, Yuhe Yu, Chen Zhang +3
In recent years, medical information technology has made it possible for electronic health record (EHR) to store fairly complete clinical data. This has brought health care into th…
Efficient Reinforcement Learning with Impaired Observability: Learning to Act with Delayed and Missing State Observations
Minshuo Chen, Jie Meng, Yu Bai +3
In real-world reinforcement learning (RL) systems, various forms of {\it impaired observability} can complicate matters. These situations arise when an agent is unable to observe t…
Chest X-ray Image Classification: A Causal Perspective
Weizhi Nie, Chen Zhang, Dan Song +4
The chest X-ray (CXR) is one of the most common and easy-to-get medical tests used to diagnose common diseases of the chest. Recently, many deep learning-based methods have been pr…
LightCurve MoE: A Dynamic Sparse Routing Mixture-of-Experts Architecture for Efficient Stellar Light Curve Classification
Cunshi Wang, Yu Bai, Xinrui Song +6
The classification of stellar light curves has become a key task in modern time-domain astronomy, fueled by the rapid growth of data from large-scale surveys such as Kepler and TES…
Breaking the Curse of Multiagency: Provably Efficient Decentralized Multi-Agent RL with Function Approximation
Yuanhao Wang, Qinghua Liu, Yu Bai +1
A unique challenge in Multi-Agent Reinforcement Learning (MARL) is the curse of multiagency, where the description length of the game as well as the complexity of many existing lea…
Offline Learning in Markov Games with General Function Approximation
Yuheng Zhang, Yu Bai, Nan Jiang
We study offline multi-agent reinforcement learning (RL) in Markov games, where the goal is to learn an approximate equilibrium -- such as Nash equilibrium and (Coarse) Correlated…
PiPAD: Pipelined and Parallel Dynamic GNN Training on GPUs
Chunyang Wang, Desen Sun, Yuebin Bai
Dynamic Graph Neural Networks (DGNNs) have been broadly applied in various real-life applications, such as link prediction and pandemic forecast, to capture both static structural…