(Q51365882)

4 April 2018

title

Construction of high-dimensional neural network potentials using environment-dependent atom pairs. (English)

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4 April 2018

author

Nongnuch Artrith

series ordinal

2

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Jörg Behler

series ordinal

3

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author name string

K V Jovan Jose

series ordinal

1

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language of work or name

English

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publication date

1 May 2012

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4 April 2018

Journal of Chemical Physics

published in

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volume

136

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issue

19

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page(s)

194111

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4 April 2018

Unified Approach for Molecular Dynamics and Density-Functional Theory

cites work

1 reference

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21 January 2018

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21 January 2018

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Ab initio potential-energy surfaces for complex, multichannel systems using modified novelty sampling and feedforward neural networks

21 January 2018

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Theoretical investigation of the dissociation dynamics of vibrationally excited vinyl bromide on an ab initio potential-energy surface obtained using modified novelty sampling and feedforward neural networks. II. Numerical application of the method

21 January 2018

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21 January 2018

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21 January 2018

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Ab initio molecular dynamics of hydrogen dissociation on metal surfaces using neural networks and novelty sampling.

21 January 2018

1 reference

Using neural networks, optimized coordinates, and high-dimensional model representations to obtain a vinyl bromide potential surface

21 January 2018

1 reference

Development of generalized potential-energy surfaces using many-body expansions, neural networks, and moiety energy approximations.

21 January 2018

1 reference

Die Berechnung optischer und elektrostatischer Gitterpotentiale

21 January 2018

1 reference

A neural network potential-energy surface for the water dimer based on environment-dependent atomic energies and charges.

21 January 2018

1 reference

A New Approach to Linear Filtering and Prediction Problems

21 January 2018

1 reference

Generalized Gradient Approximation Made Simple

21 January 2018

1 reference

Mapping Potential Energy Surfaces by Neural Networks: The ethanol/Au(111) interface

21 January 2018

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21 January 2018

Identifiers

DOI

10.1063/1.4712397

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4 April 2018

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4 April 2018