  This work introduces MiDi, a novel diffusion model for jointly generating
molecular graphs and their corresponding 3D arrangement of atoms. 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 optimize bond orders for validity.
Our code is available at github.com/cvignac/MiDi.
