… on a novel random walk model for attributed networks. The resulting optimization task is still
… of attributes in the input network. To handle large networks with numerous attributes, we …

… Therefore, we expect that the embedding H should have the subspace cluster structure.
In the attributed networks, we hope that the corresponding coefficient of H (indicating the …

… algorithm for embedding attributed networks based on the … to build an embedding algorithm
for the attributed networks by … matrix into the variational graph autoencoder. FSADA [58] …

… Network-specific variational auto-encoder for embedding in attribute networks. In Proceedings
of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), Macao, …

… Network-specific variational auto-encoder for embedding in attribute networks. In: Twenty-Eighth
International Joint Conference on Artificial Intelligence IJCAI 2019, pp. 2663–2669 (…

… Many studies on citation networks are inaccessible because … estimation that employs
structured variational inference to … In this case, embedding both attribute-observed and attribute-…

… Since random-walk based methods mainly focus on the topological structure and overlook
attributes of networks [19], some deep learning methods are proposed to overcome such a …

… (GMM) in Graph Variational Auto-Encoder to model the prior … attributes. Here, network
structure compression and node … We employ the embedding dimension of 16 for our proposed …

… ability of an extended auto-encoder and a deep neural … sources; To embed the structure
features of two social networks in … adopt an attribute auto-encoder model for two networks G A …