A valence-preserving double edge-swap diffusion model with a learned time estimator generates chemically valid molecules with property distributions closer to real molecules than JTVAE and DiGress on the GuacaMol benchmark.
Reinvent 2.0: An ai tool for de novo drug design
1 Pith paper cite this work, alongside 459 external citations. Polarity classification is still indexing.
1
Pith paper citing it
459
external citations · OpenAlex
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
A collaborative constrained graph diffusion model for the generation of realistic synthetic molecules
A valence-preserving double edge-swap diffusion model with a learned time estimator generates chemically valid molecules with property distributions closer to real molecules than JTVAE and DiGress on the GuacaMol benchmark.