Using neural networks, optimized coordinates, and high-dimensional model representations to obtain a vinyl bromide potential surface (Q46204162)

20 December 2017

title

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

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20 December 2017

author name string

Sergei Manzhos

series ordinal

1

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20 December 2017

Tucker Carrington

series ordinal

2

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20 December 2017

language of work or name

English

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publication date

1 December 2008

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20 December 2017

Journal of Chemical Physics

published in

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20 December 2017

volume

129

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issue

22

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page(s)

224104

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20 December 2017

describes a project that uses

artificial neural network

1 reference

based on heuristic

inferred from title

cites work

Potential energy surfaces for polyatomic reaction dynamics

1 reference

Constructing multidimensional molecular potential energy surfaces from ab initio data

21 January 2018

1 reference

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

21 January 2018

1 reference

Ab initio potential energy and dipole moment surfaces for H5O2 +.

21 January 2018

1 reference

Full-dimensional quantum calculations of ground-state tunneling splitting of malonaldehyde using an accurate ab initio potential energy surface

21 January 2018

1 reference

Interpolating moving least-squares methods for fitting potential energy surfaces: a strategy for efficient automatic data point placement in high dimensions

21 January 2018

1 reference

Quantum and classical studies of vibrational motion of CH5+ on a global potential energy surface obtained from a novel ab initio direct dynamics approach.

21 January 2018

1 reference

Using neural networks to represent potential surfaces as sums of products.

21 January 2018

1 reference

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

1 reference

Efficient calculation of potential energy surfaces for the generation of vibrational wave functions

21 January 2018

1 reference

Efficient correlation-corrected vibrational self-consistent field computation of OH-stretch frequencies using a low-scaling algorithm.

21 January 2018

1 reference

Efficient chemical kinetic modeling through neural network maps.

21 January 2018

1 reference

High-dimensional model representations generated from low order terms--lp-RS-HDMR.

21 January 2018

1 reference

Multicut-HDMR with an application to an ionospheric model.

21 January 2018

1 reference

Random sampling-high dimensional model representation (RS-HDMR) and orthogonality of its different order component functions

21 January 2018

1 reference

Automatic generation of potential energy and property surfaces of polyatomic molecules in normal coordinates.

21 January 2018

1 reference

Neural networks: A new method for solving chemical problems or just a passing phase?

21 January 2018

1 reference

Theoretical investigation of the dissociation dynamics of vibrationally excited vinyl bromide on an ab initio potential-energy surface obtained using modified novelty sampling and feed-forward neural networks

21 January 2018

1 reference

21 January 2018

Identifiers

DOI

10.1063/1.3021471

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20 December 2017

PubMed ID

19071904

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20 December 2017