Multiresolution equivariant graph variational autoencoder

In this paper, we propose Multiresolution Equivariant Graph Variational Autoencoders (MGVAE), the first hierarchical generative model to learn and generate graphs in a multiresolution and equivariant manner. At each resolution level, MGVAE employs higher order message passing to encode the graph whi...

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Vydané v:	Machine learning: science and technology Ročník 4; číslo 1; s. 15031 - 15054
Hlavní autori:	Hy, Truong Son, Kondor, Risi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Bristol IOP Publishing 01.03.2023
Predmet:	Coarsening graph neural networks graph variational autoencoders Graphs hierarchical generative models Image processing Learning Message passing Molecular properties molecule generation Permutations supervised and unsupervised molecular representation learning
ISSN:	2632-2153, 2632-2153
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