1 citations · 1 across the 3 of their papers we have counts for
4 papers
A Closer Look at the Application of Causal Inference in Graph Representation Learning
Hang Gao, Kunyu Li, Huang Hong +2
Modeling causal relationships in graph representation learning remains a fundamental challenge. Existing approaches often draw on theories and methods from causal inference to iden…
From Business Events to Auditable Decisions: Ontology-Governed Graph Simulation for Enterprise AI
Hongyin Zhu, Jinming Liang, Mengjun Hou +5
Existing LLM-based agent systems share a common architectural failure: they answer from the unrestricted knowledge space without first simulating how active business scenarios resh…
medDreamer: Model-Based Reinforcement Learning with Latent Imagination on Complex EHRs for Clinical Decision Support
Qianyi Xu, Gousia Habib, Feng Wu +2
Timely and personalized treatment decisions are essential across a wide range of healthcare settings where patient responses can vary significantly and evolve over time. Clinical d…
G-Transformer: Counterfactual Outcome Prediction under Dynamic and Time-varying Treatment Regimes
Hong Xiong, Feng Wu, Leon Deng +2
In the context of medical decision making, counterfactual prediction enables clinicians to predict treatment outcomes of interest under alternative courses of therapeutic actions g…