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  4. MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation
 
conference paper

MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation

Vignac, Clement
•
Osman, Nagham
•
Toni, Laura
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Koutra, D
•
Plant, C
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January 1, 2023
Machine Learning And Knowledge Discovery In Databases: Research Track, Ecml Pkdd 2023, Pt Ii
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)

This work introduces MiDi, a novel diffusion model for jointly generating molecular graphs and their corresponding 3D atom arrangements. Unlike existing methods that rely on predefined rules to determine molecular bonds based on the 3D conformation, MiDi offers an end-to-end differentiable approach that streamlines the molecule generation process. Our experimental results demonstrate the effectiveness of this approach. On the challenging GEOM-DRUGS dataset, MiDi generates 92% of stable molecules, against 6% for the previous EDM model that uses interatomic distances for bond prediction, and 40% using EDM followed by an algorithm that directly optimizes bond orders for validity. Our code is available at github.com/cvignac/MiDi.

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Type
conference paper
DOI
10.1007/978-3-031-43415-0_33
Web of Science ID

WOS:001156138300033

Author(s)
Vignac, Clement
Osman, Nagham
Toni, Laura
Frossard, Pascal  
Editors
Koutra, D
•
Plant, C
•
Rodriguez, MG
•
Baralis, E
•
Bonchi, F
Date Issued

2023-01-01

Publisher

Springer International Publishing Ag

Publisher place

Cham

Published in
Machine Learning And Knowledge Discovery In Databases: Research Track, Ecml Pkdd 2023, Pt Ii
ISBN of the book

978-3-031-43414-3

978-3-031-43415-0

Volume

14170

Start page

560

End page

576

Subjects

Technology

•

Diffusion Model

•

Drug Discovery

•

Graph Generation

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LTS4  
Event nameEvent placeEvent date
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)

Turin, ITALY

SEP 18-22, 2023

Available on Infoscience
February 23, 2024
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/205478
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