NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search

arXiv:2206.09166v2 Announce Type: replace
Abstract: Graph neural architecture search (GraphNAS) has recently aroused considerable attention in both academia and industry. However, two key challenges seriously hinder the further research of GraphNAS. First, since there is no consensus for the experimental setting, the empirical results in different research papers are often not comparable and even not reproducible, leading to unfair comparisons. Secondly, GraphNAS often needs extensive computations, which makes it highly inefficient and inaccessible to researchers without access to large-scale computation. …

abstract academia architecture arxiv attention benchmarking challenges consensus cs.lg experimental graph hinder however industry key nas neural architecture search papers research research papers results search type