1.9k citations · 2.9k across the 29 of their papers we have counts for
Showing 2022Show all
3 papers · 1 filter
cs.LG2022
DGI: Easy and Efficient Inference for GNNs
Peiqi Yin, Xiao Yan, Jinjing Zhou +5
While many systems have been developed to train Graph Neural Networks (GNNs), efficient model inference and evaluation remain to be addressed. For instance, using the widely adopte…
cs.LG2022★ 3 cited
BiFeat: Supercharge GNN Training via Graph Feature Quantization
Yuxin Ma, Ping Gong, Jun Yi +4
Graph Neural Networks (GNNs) is a promising approach for applications with nonEuclidean data. However, training GNNs on large scale graphs with hundreds of millions nodes is both r…
cs.LG2022
CEP3: Community Event Prediction with Neural Point Process on Graph
Xuhong Wang, Sirui Chen, Yixuan He +4
Many real world applications can be formulated as event forecasting on Continuous Time Dynamic Graphs (CTDGs) where the occurrence of a timed event between two entities is represen…