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cs.LG2025
Multi-Level Fusion Graph Neural Network for Molecule Property Prediction
XiaYu Liu, Chao Fan, Yang Liu +1
Accurate prediction of molecular properties is essential in drug discovery and related fields. However, existing graph neural networks (GNNs) often struggle to simultaneously captu…
cs.LG2025
Graph Positional Autoencoders as Self-supervised Learners
Yang Liu, Deyu Bo, Wenxuan Cao +3
Graph self-supervised learning seeks to learn effective graph representations without relying on labeled data. Among various approaches, graph autoencoders (GAEs) have gained signi…
cs.LG2024
Graph Distillation with Eigenbasis Matching
Yang Liu, Deyu Bo, Chuan Shi
The increasing amount of graph data places requirements on the efficient training of graph neural networks (GNNs). The emerging graph distillation (GD) tackles this challenge by di…