59 citations · 262 across the 14 of their papers we have counts for
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3 papers · 1 filter
cs.LG2021★ 57 cited
DIG: A Turnkey Library for Diving into Graph Deep Learning Research
Meng Liu, Youzhi Luo, Limei Wang +13
Although there exist several libraries for deep learning on graphs, they are aiming at implementing basic operations for graph deep learning. In the research community, implementin…
cs.LG2021★ 30 cited
GraphDF: A Discrete Flow Model for Molecular Graph Generation
Youzhi Luo, Keqiang Yan, Shuiwang Ji
We consider the problem of molecular graph generation using deep models. While graphs are discrete, most existing methods use continuous latent variables, resulting in inaccurate m…
cs.LG2021★ 20 cited
GraphEBM: Molecular Graph Generation with Energy-Based Models
Meng Liu, Keqiang Yan, Bora Oztekin +1
We note that most existing approaches for molecular graph generation fail to guarantee the intrinsic property of permutation invariance, resulting in unexpected bias in generative…