209 citations · 228 across the 8 of their papers we have counts for
8 papers
Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry
Hatem Helal, Jesun Firoz, Jenna Bilbrey +5
Molecular property calculations are the bedrock of chemical physics. High-fidelity \textit{ab initio} modeling techniques for computing the molecular properties can be prohibitivel…
Embedding Representation of Academic Heterogeneous Information Networks Based on Federated Learning
Junfu Wang, Yawen Li, Meiyu Liang +1
Academic networks in the real world can usually be portrayed as heterogeneous information networks (HINs) with multi-type, universally connected nodes and multi-relationships. Some…
Scientific Paper Classification Based on Graph Neural Network with Hypergraph Self-attention Mechanism
Jiashun Liu, Zhe Xue, Ang Li
The number of scientific papers has increased rapidly in recent years. How to make good use of scientific papers for research is very important. Through the high-quality classifica…
Spatial-Temporal Adaptive Graph Convolution with Attention Network for Traffic Forecasting
Chen Weikang, Li Yawen, Xue Zhe +2
Traffic forecasting is one canonical example of spatial-temporal learning task in Intelligent Traffic System. Existing approaches capture spatial dependency with a pre-determined m…
Searching Similarity Measure for Binarized Neural Networks
Yanfei Li, Ang Li, Huimin Yu
Being a promising model to be deployed in resource-limited devices, Binarized Neural Networks (BNNs) have drawn extensive attention from both academic and industry. However, compar…
Knowledge Graph and Accurate Portrait Construction of Scientific and Technological Academic Conferences
Runyu Yu, Zhe Xue, Ang Li
In recent years, with the continuous progress of science and technology, the number of scientific research achievements has increased rapidly. As an exchange platform and medium fo…
BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling
Cheng Wan, Youjie Li, Ang Li +2
Graph Convolutional Networks (GCNs) have emerged as the state-of-the-art method for graph-based learning tasks. However, training GCNs at scale is still challenging, hindering both…
ETA Prediction with Graph Neural Networks in Google Maps
Austin Derrow-Pinion, Jennifer She, David Wong +14
Travel-time prediction constitutes a task of high importance in transportation networks, with web mapping services like Google Maps regularly serving vast quantities of travel time…