1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2023
A Metadata-Driven Approach to Understand Graph Neural Networks
Ting Wei Li, Qiaozhu Mei, Jiaqi Ma
Graph Neural Networks (GNNs) have achieved remarkable success in various applications, but their performance can be sensitive to specific data properties of the graph datasets they…
cs.LG2022★ 1 cited
Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks
Jiaqi Ma, Xingjian Zhang, Hezheng Fan +6
Establishing open and general benchmarks has been a critical driving force behind the success of modern machine learning techniques. As machine learning is being applied to broader…