Publications
Found 12 results
Filters: Author is Simon Axelrod [Clear All Filters]
“Mapping the space of photoswitchable ligands and photodruggable proteins with computational modeling”, J. Chem. Inf. Model., 2023.
, “Molecular machine learning with conformer ensembles”, Machine Learning: Science and Technology, 2023.
, , “Bottlebrush polymers with flexible enantiomeric side chains display differential biological properties”, Nature Chemistry, vol. 14, pp. 85-93, 2022.
, “Excited state non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential”, Nature Communications, vol. 13, p. 3440, 2022.
, “GEOM: Energy-annotated molecular conformations for property prediction and molecular generation”, Scientific Data, vol. 9, p. 185, 2022.
, “Learning Matter: Materials Design with Machine Learning and Atomistic Simulations”, Accounts of Materials Research, 2022.
, “Neural Scaling of Deep Chemical Models”, ChemRxiv, 2022.
, “Synthetic Glycomacromolecules of Defined Valency, Absolute Configuration, and Topology Distinguish between Human Lectins”, JACS Au, vol. 1(10), pp. 1621–1630, 2021.
, “Active Learning Accelerates Ab Initio Molecular Dynamics on Pericyclic Reactive Energy Surfaces”, Chem, vol. 7(3), pp. 738-51, 2020.
, “Differentiable Molecular Simulations for Control and Learning”, arXiv:2003.00868, 2020.
, “Temperature-transferable coarse-graining of ionic liquids with dual graph convolutional neural networks”, The Journal of Chemical Physics, vol. 153, p. 164501, 2020.
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