Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox

Picture for Hongkuan Zhou

SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings


Sep 09, 2021
Hongkuan Zhou, James Orme-Rogers, Rajgopal Kannan, Viktor Prasanna


  Access Paper or Ask Questions

Accelerating Large Scale Real-Time GNN Inference using Channel Pruning


May 10, 2021
Hongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, Viktor Prasanna


  Access Paper or Ask Questions

Accurate, Efficient and Scalable Training of Graph Neural Networks


Oct 05, 2020
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor Prasanna

* Journal of Parallel and Distributed Computing, Volume 147, January 2021, Pages 166-183 
* 43 pages, 8 figures. arXiv admin note: text overlap with arXiv:1810.11899 

  Access Paper or Ask Questions

GraphSAINT: Graph Sampling Based Inductive Learning Method


Jul 10, 2019
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor Prasanna

* 16 pages 

  Access Paper or Ask Questions

Accurate, Efficient and Scalable Graph Embedding


Oct 30, 2018
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor Prasanna

* 10 pages 

  Access Paper or Ask Questions