Graph Energy-based Model for Molecular Graph Generation

Abstract

We present Graph Energy-based Model (GEM), an energy-based model for molecular graph generation. GEM uses dequantization and gradient symmetrization to incorporate generation by stochastic gradient Langevin dynamics for graph representation that is discrete and includes symmetric constraint. Experimental results show that can comparably design compounds as other deep generative approaches.

Tasks

Reproductions