publications

2021

2021

1. Using Sparse Spectral Shifts in Graph CNNs

   Austin Lin , John Shi , Mark Cheung , and 1 more author

   In 55th Asilomar Conference on Signals, Systems, and Computers , Nov 2021

   submitted
2. Graph Classification: Tradeoffs between Deep Neural Network Architecture and Graph Topology

   Mark Cheung , and José M. F. Moura

   In 55th Asilomar Conference on Signals, Systems, and Computers , Nov 2021

   submitted

2020

2020

1. A Dual Approach to Graph CNNs

   John Shi , Mark Cheung , Wendy Summer , and 1 more author

   In 54th Asilomar Conference on Signals, Systems, and Computers , Nov 2020
2. Graph Neural Networks for COVID-19 Drug Discovery

   Mark Cheung , and José M. F. Moura

   Artificial Intelligence for Data Discovery and Reuse (AIDR) and Open Science Symposium (OSS), Oct 2020
3. Evaluating Effectiveness of Graph Structures

   Yao Jiang , John Shi , Mark Cheung , and 2 more authors

   In 54th Asilomar Conference on Signals, Systems, and Computers , Nov 2020
4. Graph Signal Processing and Deep Learning: Convolution, Pooling, and Topology

   Mark Cheung , John Shi , Oren Wright , and 3 more authors

   IEEE SPM Special Issue on Graph Signal Processing: Foundations and Emerging Directions, Nov 2020

2019

2019

1. Pooling in graph convolutional neural networks

   Mark Cheung , John Shi , Oren Wright , and 2 more authors

   In 53rd Asilomar Conference on Signals, Systems, and Computers , Nov 2019

2018

2018

1. Classification with Vertex-Based Graph Convolutional Neural Networks

   John Shi , Mark Cheung , Jian Du , and 1 more author

   In 52nd Asilomar Conference on Signals, Systems, and Computers , Nov 2018
2. Contrastive Structured Anomaly Detection for Gaussian Graphical Models

   A. Maurya , and M. Cheung

   In 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) , Nov 2018