14 citations · 33 across the 4 of their papers we have counts for
4 papers
Uncertainty-Aware Graph Neural Networks: A Multi-Hop Evidence Fusion Approach
Qingfeng Chen, Shiyuan Li, Yixin Liu +3
Graph neural networks (GNNs) excel in graph representation learning by integrating graph structure and node features. Existing GNNs, unfortunately, fail to account for the uncertai…
Large Language Models in Drug Discovery and Development: From Disease Mechanisms to Clinical Trials
Yizhen Zheng, Huan Yee Koh, Maddie Yang +5
The integration of Large Language Models (LLMs) into the drug discovery and development field marks a significant paradigm shift, offering novel methodologies for understanding dis…
Noise-Resilient Unsupervised Graph Representation Learning via Multi-Hop Feature Quality Estimation
Shiyuan Li, Yixin Liu, Qingfeng Chen +2
Unsupervised graph representation learning (UGRL) based on graph neural networks (GNNs), has received increasing attention owing to its efficacy in handling graph-structured data.…
Large Language Models for Scientific Synthesis, Inference and Explanation
Yizhen Zheng, Huan Yee Koh, Jiaxin Ju +4
Large language models are a form of artificial intelligence systems whose primary knowledge consists of the statistical patterns, semantic relationships, and syntactical structures…