Justin S Smith (J S Smith)

ORCID

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 19

Top Venues

Nature chemistry

Nature computational science

The Journal of chemical physics

Chemical science

Los Alamos National Laboratory

This page only lists publications with an associated author ORCID identifier.

Affiliation History

Los Alamos National Laboratory Jan 02 2018

United States

Graduate Research Associate :: T-CNLS: CENTER FOR NONLINEAR STUDIES

Publications

Shuhao Zhang, Małgorzata Zofia Makoś, Ryan B Jadrich, Elfi Kraka, Kipton Barros, Benjamin T Nebgen, Sergei Tretiak, Oleksandr Isaev, Nicholas Lubbers, Richard A Messerly, Justin S Smith
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential. Nature chemistry 16 (5) (2024)
Shuhao Zhang, Małgorzata Zofia Makoś, Ryan B Jadrich, Elfi Kraka, Kipton Barros, Benjamin T Nebgen, Sergei Tretiak, Oleksandr Isaev, Nicholas Lubbers, Richard A Messerly, Justin S Smith
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential. Nature chemistry (2024)
Shuhao Zhang, Małgorzata Zofia Makoś, Ryan B Jadrich, Elfi Kraka, Kipton Barros, Benjamin T Nebgen, Sergei Tretiak, Oleksandr Isaev, Nicholas Lubbers, Richard A Messerly, Justin S Smith
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential. Nature chemistry 16 (5) (2024)
Shuhao Zhang, Małgorzata Zofia Makoś, Ryan B Jadrich, Elfi Kraka, Kipton Barros, Benjamin T Nebgen, Sergei Tretiak, Oleksandr Isaev, Nicholas Lubbers, Richard A Messerly, Justin S Smith
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential. Nature chemistry 16 (5) (2024)
Maksim Kulichenko, Kipton Barros, Nicholas Lubbers, Ying Wai Li, Richard Messerly, Sergei Tretiak, Justin S Smith, Benjamin T Nebgen
Uncertainty-driven dynamics for active learning of interatomic potentials. Nature computational science 3 (3) (2023)
Michael Chigaev, Justin S Smith, Steven Anaya, Benjamin T Nebgen, Matthew Bettencourt, Kipton Barros, Nicholas Lubbers
Lightweight and effective tensor sensitivity for atomistic neural networks. The Journal of chemical physics 158 (18) (2023)
Maksim Kulichenko, Kipton Barros, Nicholas Lubbers, Ying Wai Li, Richard Messerly, Sergei Tretiak, Justin S Smith, Benjamin T Nebgen
Uncertainty-driven dynamics for active learning of interatomic potentials. Nature computational science 3 (3) (2023)
Maksim Kulichenko, Kipton Barros, Nicholas Lubbers, Ying Wai Li, Richard Messerly, Sergei Tretiak, Justin S Smith, Benjamin T Nebgen
Uncertainty-driven dynamics for active learning of interatomic potentials. Nature computational science 3 (3) (2023)
Maksim Kulichenko, Kipton Barros, Nicholas Lubbers, Ying Wai Li, Richard Messerly, Sergei Tretiak, Justin S Smith, Benjamin T Nebgen
Uncertainty-driven dynamics for active learning of interatomic potentials. Nature computational science 3 (3) (2023)
Nikita Fedik, Roman Zubatyuk, Maksim Kulichenko, Nicholas Lubbers, Justin S Smith, Benjamin T Nebgen, Richard A Messerly, Ying Wai Li, Alexander I Boldyrev, Kipton Barros, Oleksandr Isaev, Sergei Tretiak
Extending machine learning beyond interatomic potentials for predicting molecular properties. Nature reviews. Chemistry 6 (9) (2022)
Nikita Fedik, Roman Zubatyuk, Maksim Kulichenko, Nicholas Lubbers, Justin S Smith, Benjamin T Nebgen, Richard A Messerly, Ying Wai Li, Alexander I Boldyrev, Kipton Barros, Oleksandr Isaev, Sergei Tretiak
Extending machine learning beyond interatomic potentials for predicting molecular properties. Nature reviews. Chemistry 6 (9) (2022)
Justin S Smith, Benjamin T Nebgen, Nithin Mathew, Jie Chen, Nicholas Lubbers, Leonid Burakovsky, Sergei Tretiak, Hai Ah Nam, Timothy C Germann, Saryu Fensin, Kipton Barros
Automated discovery of a robust interatomic potential for aluminum. Nature communications 12 (1) (2021)
Andrew E Sifain, Levi Lystrom, Richard A Messerly, Justin S Smith, Benjamin T Nebgen, Kipton Barros, Sergei Tretiak, Nicholas Lubbers, Brendan J Gifford
Predicting phosphorescence energies and inferring wavefunction localization with machine learning. Chemical science 12 (30) (2021)
Roman Zubatyuk, Justin S Smith, Benjamin T Nebgen, Sergei Tretiak, Oleksandr Isaev
Teaching a neural network to attach and detach electrons from molecules. Nature communications 12 (1) (2021)
Justin S Smith, Roman Zubatyuk, Benjamin Nebgen, Nicholas Lubbers, Kipton Barros, Adrian E Roitberg, Oleksandr Isaev, Sergei Tretiak
The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules. Scientific data 7 (1) (2020)
Nicholas Lubbers, Justin S Smith, Kipton Barros
Hierarchical modeling of molecular energies using a deep neural network. The Journal of chemical physics 148 (24) (2018)
Justin S Smith, Ben Nebgen, Nicholas Lubbers, Oleksandr Isaev, Adrian E Roitberg
Less is more: Sampling chemical space with active learning. The Journal of chemical physics 148 (24) (2018)
Justin S Smith, Oleksandr Isaev, Adrian E Roitberg
ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost. Chemical science 8 (4) (2017)
Justin S Smith, Olexandr Isayev, Adrian E Roitberg
ANI-1, A data set of 20 million calculated off-equilibrium conformations for organic molecules. Scientific data 4 (2017)

Justin S Smith.css-eqlu8i{font-size:small;padding-left:4px;} (J S Smith)

Publication Activity (10 Years)

Top Topics

Top Venues

Justin S Smith (J S Smith)