95 citations · 252 across the 15 of their papers we have counts for
15 papers
Local-to-global Perspectives on Graph Neural Networks
Chen Cai
This thesis presents a local-to-global perspective on graph neural networks (GNN), the leading architecture to process graph-structured data. After categorizing GNN into local Mess…
On the Connection Between MPNN and Graph Transformer
Chen Cai, Truong Son Hy, Rose Yu +1
Graph Transformer (GT) recently has emerged as a new paradigm of graph learning algorithms, outperforming the previously popular Message Passing Neural Network (MPNN) on multiple b…
Generative Coarse-Graining of Molecular Conformations
Wujie Wang, Minkai Xu, Chen Cai +5
Coarse-graining (CG) of molecular simulations simplifies the particle representation by grouping selected atoms into pseudo-beads and drastically accelerates simulation. However, s…
Convergence of Invariant Graph Networks
Chen Cai, Yusu Wang
Although theoretical properties such as expressive power and over-smoothing of graph neural networks (GNN) have been extensively studied recently, its convergence property is a rel…
Traffic4cast -- Large-scale Traffic Prediction using 3DResNet and Sparse-UNet
Bo Wang, Reza Mohajerpoor, Chen Cai +2
The IARAI competition Traffic4cast 2021 aims to predict short-term city-wide high-resolution traffic states given the static and dynamic traffic information obtained previously. Th…
Equivariant Subgraph Aggregation Networks
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim +5
Message-passing neural networks (MPNNs) are the leading architecture for deep learning on graph-structured data, in large part due to their simplicity and scalability. Unfortunatel…