1 citations · 2 across the 7 of their papers we have counts for
7 papers
Context-aware Graph Causality Inference for Few-Shot Molecular Property Prediction
Van Thuy Hoang, O-Joun Lee
Molecular property prediction is becoming one of the major applications of graph learning in Web-based services, e.g., online protein structure prediction and drug discovery. A key…
Pre-training Graph Neural Networks on 2D and 3D Molecular Structures by using Multi-View Conditional Information Bottleneck
Van Thuy Hoang, O-Joun Lee
Recent pre-training strategies for molecular graphs have attempted to use 2D and 3D molecular views as both inputs and self-supervised signals, primarily aligning graph-level repre…
Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention
Van Thuy Hoang, Hyeon-Ju Jeon, O-Joun Lee
Graph Neural Networks (GNNs) update node representations through message passing, which is primarily based on the homophily principle, assuming that adjacent nodes share similar fe…
Halal or Not: Knowledge Graph Completion for Predicting Cultural Appropriateness of Daily Products
Van Thuy Hoang, Tien-Bach-Thanh Do, Jinho Seo +5
The growing demand for halal cosmetic products has exposed significant challenges, especially in Muslim-majority countries. Recently, various machine learning-based strategies, e.g…
Pre-training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck
Van Thuy Hoang, O-Joun Lee
This study aims to build a pre-trained Graph Neural Network (GNN) model on molecules without human annotations or prior knowledge. Although various attempts have been proposed to o…
A Survey on Structure-Preserving Graph Transformers
Van Thuy Hoang, O-Joun Lee
The transformer architecture has shown remarkable success in various domains, such as natural language processing and computer vision. When it comes to graph learning, transformers…
Mitigating Degree Biases in Message Passing Mechanism by Utilizing Community Structures
Van Thuy Hoang, O-Joun Lee
This study utilizes community structures to address node degree biases in message-passing (MP) via learnable graph augmentations and novel graph transformers. Recent augmentation-b…