Web: http://arxiv.org/abs/2206.08582

June 20, 2022, 1:10 a.m. | Wentao Zhang, Zheyu Lin, Yu Shen, Yang Li, Zhi Yang, Bin Cui

cs.LG updates on arXiv.org arxiv.org

Graph neural networks (GNNs) have been intensively applied to various
graph-based applications. Despite their success, manually designing the
well-behaved GNNs requires immense human expertise. And thus it is inefficient
to discover the potentially optimal data-specific GNN architecture. This paper
proposes DFG-NAS, a new neural architecture search (NAS) method that enables
the automatic search of very deep and flexible GNN architectures. Unlike most
existing methods that focus on micro-architectures, DFG-NAS highlights another
level of design: the search for macro-architectures on how …

architecture arxiv deep graph lg nas neural neural architecture search search

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