Accurate and transferable multitask prediction of chemical properties with an atoms-in-molecules neural network-Reference-Cited by-同舟云学术

Accurate and transferable multitask prediction of chemical properties with an atoms-in-molecules neural network

Published:2019-08-02 Issue:8 Volume:5 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Zubatyuk Roman¹²³^ORCID,Smith Justin S.²⁴,Leszczynski Jerzy³^ORCID,Isayev Olexandr¹^ORCID

Affiliation:

1. Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

2. Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.

3. Interdisciplinary Nanotoxicity Center, Department of Chemistry, Physics and Atmospheric Sciences, Jackson State University, Jackson, MS 39217, USA.

4. Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.

Abstract

We introduce a modular, chemically inspired deep neural network model for prediction of several atomic and molecular properties.

Funder

National Science Foundation

Office of Naval Research

NNSA

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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