DiGress: discrete denoising diffusion for graph generation

October 28, 2022

DiGress generates graphs by denoising in discrete space instead of lifting the problem into continuous space. The discrete formulation keeps node and edge types categorical the whole way through, which enables computing rich features and was the first graph diffusion paper to scale to the MOSES and Guacamol molecular benchmarks. Co-first author; cited 800+ times as of June 2026, about 140 of those flagged as highly influential. Citation counts are from Google Scholar, as of June 2026.