Papers › Equivariant Diffusion for Molecule Generation in 3D
Equivariant Diffusion for Molecule Generation in 3D
Emiel Hoogeboom, Victor Garcia Satorras, Clément Vignac, Max Welling
This work introduces a diffusion model for molecule generation in 3D that is equivariant to Euclidean transformations. Our E(3) Equivariant Diffusion Model (EDM) learns to denoise a diffusion process with an equivariant network that jointly operates on both continuous (atom coordinates) and categorical features (atom types). In addition, we provide a probabilistic analysis which admits likelihood computation of molecules using our model. Experimentally, the proposed method significantly outperforms previous 3D molecular generative methods regarding the quality of generated samples and efficiency at training time.
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Code
Syntology Ran 7 of 13 code samples harvested from 2 repositories linked to this paper; 6 have no recorded run. Of those that ran: 3 ran · our draft was wrong; 4 ran with no contract checked.
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Code Syntology ran Syntology
13 samples harvested; 7 ran; 0 honoured the contract we drafted; 6 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.
Licence: 2 of the 13 samples are pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.
Harvested from 2 repositories linked to this paper, official or community; each sample names its own and says which. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Unconditional Molecule Generation | QM9 | EDM | PoseBusters Internal Energy | 94.88 | #3 of 4 | Archive leaderboard | report |
| Unconditional Molecule Generation | QM9 | EDM | Validity | 91.90 | #3 of 4 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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