94 citations · 274 across the 10 of their papers we have counts for
4 papers · 1 filter
Molecular machine learning with conformer ensembles
Simon Axelrod, Rafael Gomez-Bombarelli
Virtual screening can accelerate drug discovery by identifying promising candidates for experimental evaluation. Machine learning is a powerful method for screening, as it can lear…
Temperature-transferable coarse-graining of ionic liquids with dual graph convolutional neural networks
Jurgis Ruza, Wujie Wang, Daniel Schwalbe-Koda +3
Computer simulations can provide mechanistic insight into ionic liquids (ILs) and predict the properties of experimentally unrealized ion combinations. However, ILs suffer from a p…
GEOM: Energy-annotated molecular conformations for property prediction and molecular generation
Simon Axelrod, Rafael Gomez-Bombarelli
Machine learning (ML) outperforms traditional approaches in many molecular design tasks. ML models usually predict molecular properties from a 2D chemical graph or a single 3D stru…
Differentiable Molecular Simulations for Control and Learning
Wujie Wang, Simon Axelrod, Rafael Gómez-Bombarelli
Molecular dynamics simulations use statistical mechanics at the atomistic scale to enable both the elucidation of fundamental mechanisms and the engineering of matter for desired t…