5 citations · 7 across the 3 of their papers we have counts for
4 papers
MAG-GNN: Reinforcement Learning Boosted Graph Neural Network
Lecheng Kong, Jiarui Feng, Hao Liu +3
While Graph Neural Networks (GNNs) recently became powerful tools in graph learning tasks, considerable efforts have been spent on improving GNNs' structural encoding ability. A pa…
Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node Tasks
Hao Liu, Jiarui Feng, Lecheng Kong +3
Graph Neural Networks (GNNs) have become popular in Graph Representation Learning (GRL). One fundamental application is few-shot node classification. Most existing methods follow t…
Time Associated Meta Learning for Clinical Prediction
Hao Liu, Muhan Zhang, Zehao Dong +5
Rich Electronic Health Records (EHR), have created opportunities to improve clinical processes using machine learning methods. Prediction of the same patient events at different ti…
A Multi-View Joint Learning Framework for Embedding Clinical Codes and Text Using Graph Neural Networks
Lecheng Kong, Christopher King, Bradley Fritz +1
Learning to represent free text is a core task in many clinical machine learning (ML) applications, as clinical text contains observations and plans not otherwise available for inf…