Simon Axelrod

11 papers Journal 10Unranked 1
YearRankTypeTitle / Venue / Authors
2023 J jnl
Mapping the Space of Photoswitchable Ligands and Photodruggable Proteins with Computational Modeling.
J. Chem. Inf. Model.
Simon Axelrod, Eugene Shakhnovich, Rafael Gómez-Bombarelli
2023 J jnl
Molecular machine learning with conformer ensembles.
Mach. Learn. Sci. Technol.
Simon Axelrod, Rafael Gómez-Bombarelli
2023 J jnl
Natural Quantum Monte Carlo Computation of Excited States.
CoRR
David Pfau, Simon Axelrod, Halvard Sutterud, Ingrid von Glehn, James S. Spencer
2023 J jnl
Neural scaling of deep chemical models.
Nat. Mac. Intell.
Nathan C. Frey, Ryan Soklaski, Simon Axelrod, Siddharth Samsi, Rafael Gómez-Bombarelli, Connor W. Coley, Vijay Gadepally
2022 — conf
Energy-aware neural architecture selection and hyperparameter optimization.
IPDPS Workshops
Nathan C. Frey, Dan Zhao, Simon Axelrod, Michael Jones, David Bestor, Vijay Gadepally, Rafael Gómez-Bombarelli, Siddharth Samsi
2022 J jnl
Learned Force Fields Are Ready For Ground State Catalyst Discovery.
CoRR
Michael Schaarschmidt, Morgane Riviere, Alex M. Ganose, James S. Spencer, Alexander L. Gaunt, James Kirkpatrick, Simon Axelrod, Peter W. Battaglia, Jonathan Godwin
2022 J jnl
Thermal half-lives of azobenzene derivatives: virtual screening based on intersystem crossing using a machine learning potential.
CoRR
Simon Axelrod, Eugene Shakhnovich, Rafael Gómez-Bombarelli
2021 J jnl
Excited state, non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential.
CoRR
Simon Axelrod, Eugene Shakhnovich, Rafael Gómez-Bombarelli
2020 J jnl
Differentiable Molecular Simulations for Control and Learning.
CoRR
Wujie Wang, Simon Axelrod, Rafael Gómez-Bombarelli
2020 J jnl
GEOM: Energy-annotated molecular conformations for property prediction and molecular generation.
CoRR
Simon Axelrod, Rafael Gómez-Bombarelli
2020 J jnl
Molecular machine learning with conformer ensembles.
CoRR
Simon Axelrod, Rafael Gómez-Bombarelli