37 citations · 169 across the 20 of their papers we have counts for
4 papers · 1 filter
DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs
Da Zheng, Chao Ma, Minjie Wang +6
Graph neural networks (GNN) have shown great success in learning from graph-structured data. They are widely used in various applications, such as recommendation, fraud detection,…
COVID-19 Knowledge Graph: Accelerating Information Retrieval and Discovery for Scientific Literature
Colby Wise, Vassilis N. Ioannidis, Miguel Romero Calvo +6
The coronavirus disease (COVID-19) has claimed the lives of over 350,000 people and infected more than 6 million people worldwide. Several search engines have surfaced to provide r…
Repurpose Open Data to Discover Therapeutics for COVID-19 using Deep Learning
Xiangxiang Zeng, Xiang Song, Tengfei Ma +6
There have been more than 850,000 confirmed cases and over 48,000 deaths from the human coronavirus disease 2019 (COVID-19) pandemic, caused by novel severe acute respiratory syndr…
DGL-KE: Training Knowledge Graph Embeddings at Scale
Da Zheng, Xiang Song, Chao Ma +6
Knowledge graphs have emerged as a key abstraction for organizing information in diverse domains and their embeddings are increasingly used to harness their information in various…