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7 results in Authors: Benjamin Nebgen

Physical Chemistry

Working Paper

Challenges and Opportunities for Machine Learning Potentials in Transition Path Sampling: Alanine Dipeptide and Azobenzene Studies

Nikita Fedik, Wei Li, Nicholas Lubbers, Benjamin Nebgen, Sergei Tretiak, Ying Wai Li

Version 2 posted 05 August 2024

421

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Theoretical and Computational Chemistry

Working Paper

The ANI-1ccx and ANI-1x Data Sets, Coupled-Cluster and Density Functional Theory Properties for Molecules

Justin S. Smith, Roman Zubatyuk, Benjamin T. Nebgen, Nicholas Lubbers, Kipton Barros, Adrian Roitberg, Olexandr Isayev, Sergei Tretiak

Version 2 posted 28 April 2020

1,799

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Theoretical and Computational Chemistry

Working Paper

Discovering a Transferable Charge Assignment Model Using Machine Learning

Andrew E. Sifain, Nicholas Lubbers, Benjamin T. Nebgen, Justin S. Smith, Andrey Y. Lokhov, Olexandr Isayev, Adrian E. Roitberg, Kipton Barros, Sergei Tretiak

Version 1 posted 22 June 2018

1,455

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Physical Chemistry

Working Paper

Predicting Phosphorescence Energies and Inferring Wavefunction Localization with Machine Learning

Andrew E. Sifain, Levi Lystrom, Richard A. Messerly, Justin Smith, Benjamin Nebgen, Kipton Barros, Sergei Tretiak, Nicholas Lubbers, Brendan J. Gifford

Version 3 posted 30 June 2021

737

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Theoretical and Computational Chemistry

Working Paper

Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning

Justin S Smith, Benjamin T. Nebgen, Roman Zubatyuk, Nicholas Lubbers, Christian Devereux, Kipton Barros, Sergei Tretiak, Olexandr Isayev, Adrian Roitberg

Version 2 posted 14 June 2019

4,833

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Citations

Theoretical and Computational Chemistry

Working Paper

Exploring the frontiers of chemistry with a general reactive machine learning potential

SHUHAO ZHANG, Małgorzata Makoś, Ryan Jadrich, Elfi Kraka, Kipton Barros, Benjamin Nebgen, Sergei Tretiak, Olexandr Isayev, Nicholas Lubbers, Richard Messerly, Justin Smith

Version 3 posted 17 April 2023

2,273

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Citations

Theoretical and Computational Chemistry

Working Paper

Teaching a Neural Network to Attach and Detach Electrons from Molecules

Roman Zubatyuk, Justin Smith, Benjamin T. Nebgen, Sergei Tretiak, Olexandr Isayev

Version 2 posted 12 April 2021

1,648

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7 results in Benjamin Nebgen in Authors: Benjamin Nebgen

Challenges and Opportunities for Machine Learning Potentials in Transition Path Sampling: Alanine Dipeptide and Azobenzene Studies

The ANI-1ccx and ANI-1x Data Sets, Coupled-Cluster and Density Functional Theory Properties for Molecules

Discovering a Transferable Charge Assignment Model Using Machine Learning

Predicting Phosphorescence Energies and Inferring Wavefunction Localization with Machine Learning

Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning

Exploring the frontiers of chemistry with a general reactive machine learning potential

Teaching a Neural Network to Attach and Detach Electrons from Molecules

7 results in Authors: Benjamin Nebgen