244 citations · 377 across the 9 of their papers we have counts for
3 papers · 1 filter
Will More Expressive Graph Neural Networks do Better on Generative Tasks?
Xiandong Zou, Xiangyu Zhao, Pietro Liò +1
Graph generation poses a significant challenge as it involves predicting a complete graph with multiple nodes and edges based on simply a given label. This task also carries fundam…
Hybrid Graph: A Unified Graph Representation with Datasets and Benchmarks for Complex Graphs
Zehui Li, Xiangyu Zhao, Mingzhu Shen +3
Graphs are widely used to encapsulate a variety of data formats, but real-world networks often involve complex node relations beyond only being pairwise. While hypergraphs and hier…
Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration
Xiangyu Zhao, Hannes Stärk, Dominique Beaini +2
It has been increasingly demanding to develop reliable methods to evaluate the progress of Graph Neural Network (GNN) research for molecular representation learning. Existing GNN b…