Graph Normalizing Flows

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), pp. 13556-13566, 2019.

Cited by: 30|Bibtex|Views171
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Other Links: dblp.uni-trier.de|arxiv.org

Abstract:

We introduce graph normalizing flows: a new, reversible graph neural network model for prediction and generation. On supervised tasks, graph normalizing flows perform similarly to message passing neural networks, but at a significantly reduced memory footprint, allowing them to scale to larger graphs. In the unsupervised case, we combine ...More

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