554 citations · 711 across the 6 of their papers we have counts for
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cs.LG2018
Representation Learning for Spatial Graphs
Zheng Wang, Ce Ju, Gao Cong +1
Recently, the topic of graph representation learning has received plenty of attention. Existing approaches usually focus on structural properties only and thus they are not suffici…
cs.LG2018
Heron Inference for Bayesian Graphical Models
Daniel Rugeles, Zhen Hai, Gao Cong +1
Bayesian graphical models have been shown to be a powerful tool for discovering uncertainty and causal structure from real-world data in many application fields. Current inference…