11 citations · 16 across the 2 of their papers we have counts for
2 papers
cs.LG2020★ 5 cited
Graph Autoencoders with Deconvolutional Networks
Jia Li, Tomas Yu, Da-Cheng Juan +3
Recent studies have indicated that Graph Convolutional Networks (GCNs) act as a \emph{low pass} filter in spectral domain and encode smoothed node representations. In this paper, w…
cs.LG2020★ 11 cited
Dirichlet Graph Variational Autoencoder
Jia Li, Tomasyu Yu, Jiajin Li +5
Graph Neural Networks (GNNs) and Variational Autoencoders (VAEs) have been widely used in modeling and generating graphs with latent factors. However, there is no clear explanation…