Simon Axelrod

Publication Activity (10 Years)

Years Active: 2020-2023
Publications (10 Years): 11

Top Topics

Neural Architecture

Computational Modeling

Top Venues

Mach. Learn. Sci. Technol.

Nat. Mac. Intell.

J. Chem. Inf. Model.

Publications

Simon Axelrod, Rafael Gómez-Bombarelli
Molecular machine learning with conformer ensembles. Mach. Learn. Sci. Technol. 4 (3) (2023)
Simon Axelrod, Eugene Shakhnovich, Rafael Gómez-Bombarelli
Mapping the Space of Photoswitchable Ligands and Photodruggable Proteins with Computational Modeling. J. Chem. Inf. Model. 63 (18) (2023)
Nathan C. Frey, Ryan Soklaski, Simon Axelrod, Siddharth Samsi, Rafael Gómez-Bombarelli, Connor W. Coley, Vijay Gadepally
Neural scaling of deep chemical models. Nat. Mac. Intell. 5 (11) (2023)
David Pfau, Simon Axelrod, Halvard Sutterud, Ingrid von Glehn, James S. Spencer
Natural Quantum Monte Carlo Computation of Excited States. CoRR (2023)
Michael Schaarschmidt, Morgane Riviere, Alex M. Ganose, James S. Spencer, Alexander L. Gaunt, James Kirkpatrick, Simon Axelrod, Peter W. Battaglia, Jonathan Godwin
Learned Force Fields Are Ready For Ground State Catalyst Discovery. CoRR (2022)
Simon Axelrod, Eugene Shakhnovich, Rafael Gómez-Bombarelli
Thermal half-lives of azobenzene derivatives: virtual screening based on intersystem crossing using a machine learning potential. CoRR (2022)
Nathan C. Frey, Dan Zhao, Simon Axelrod, Michael Jones, David Bestor, Vijay Gadepally, Rafael Gómez-Bombarelli, Siddharth Samsi
Energy-aware neural architecture selection and hyperparameter optimization. IPDPS Workshops (2022)
Simon Axelrod, Eugene Shakhnovich, Rafael Gómez-Bombarelli
Excited state, non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential. CoRR (2021)
Wujie Wang, Simon Axelrod, Rafael Gómez-Bombarelli
Differentiable Molecular Simulations for Control and Learning. CoRR (2020)
Simon Axelrod, Rafael Gómez-Bombarelli
GEOM: Energy-annotated molecular conformations for property prediction and molecular generation. CoRR (2020)
Simon Axelrod, Rafael Gómez-Bombarelli
Molecular machine learning with conformer ensembles. CoRR (2020)