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The Journal of Chemical Physics
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April 15, 2006
Molecular dynamics investigations of the dissociation of SiO2 on an ab initio potential energy surface obtained using neural network methods
Paras M Agrawal, Lionel M Raff, Martin T Hagan, et al.
The Journal of Chemical Physics
|
June 3, 2010
Input vector optimization of feed-forward neural networks for fitting ab initio potential-energy databases
M Malshe, L M Raff, M Hagan, et al.
The Journal of Chemical Physics
|
October 2, 2009
Accurate prediction of higher-level electronic structure energies for large databases using neural networks, Hartree-Fock energies, and small subsets of the database
M Malshe, A Pukrittayakamee, L M Raff, et al.
The Journal of Chemical Physics
|
August 7, 2008
Parametrization of analytic interatomic potential functions using neural networks
M Malshe, R Narulkar, L M Raff, et al.
Cancer
|
August 15, 1983
Angiosarcoma of the superior vena cava
R P Abratt, M Williams, M Raff, et al.
The American Journal of the Medical Sciences
|
November 1, 1976
A double blind study of the effects of zinc sulfate on taste and smell dysfunction
R I Henkin, P J Schecter, W T Friedewald, et al.
The Journal of Chemical Physics
|
October 9, 2007
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
M Malshe, L M Raff, M G Rockley, et al.
The Journal of Chemical Physics
|
April 20, 2005
Ab initio potential-energy surfaces for complex, multichannel systems using modified novelty sampling and feedforward neural networks
L M Raff, M Malshe, M Hagan, et al.
The Journal of Chemical Physics
|
April 10, 2009
Simultaneous fitting of a potential-energy surface and its corresponding force fields using feedforward neural networks
A Pukrittayakamee, M Malshe, M Hagan, et al.
The Journal of Chemical Physics
|
February 14, 2006
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
D I Doughan, L M Raff, M G Rockley, et al.
Page
of 10
Search research articles
Search
Showing results (71-80 of 93) with videos related to
Sort By:
Page
of 10
The Journal of Chemical Physics
|
April 15, 2006
Molecular dynamics investigations of the dissociation of SiO2 on an ab initio potential energy surface obtained using neural network methods
Paras M Agrawal, Lionel M Raff, Martin T Hagan, et al.
The Journal of Chemical Physics
|
June 3, 2010
Input vector optimization of feed-forward neural networks for fitting ab initio potential-energy databases
M Malshe, L M Raff, M Hagan, et al.
The Journal of Chemical Physics
|
October 2, 2009
Accurate prediction of higher-level electronic structure energies for large databases using neural networks, Hartree-Fock energies, and small subsets of the database
M Malshe, A Pukrittayakamee, L M Raff, et al.
The Journal of Chemical Physics
|
August 7, 2008
Parametrization of analytic interatomic potential functions using neural networks
M Malshe, R Narulkar, L M Raff, et al.
Cancer
|
August 15, 1983
Angiosarcoma of the superior vena cava
R P Abratt, M Williams, M Raff, et al.
The American Journal of the Medical Sciences
|
November 1, 1976
A double blind study of the effects of zinc sulfate on taste and smell dysfunction
R I Henkin, P J Schecter, W T Friedewald, et al.
The Journal of Chemical Physics
|
October 9, 2007
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
M Malshe, L M Raff, M G Rockley, et al.
The Journal of Chemical Physics
|
April 20, 2005
Ab initio potential-energy surfaces for complex, multichannel systems using modified novelty sampling and feedforward neural networks
L M Raff, M Malshe, M Hagan, et al.
The Journal of Chemical Physics
|
April 10, 2009
Simultaneous fitting of a potential-energy surface and its corresponding force fields using feedforward neural networks
A Pukrittayakamee, M Malshe, M Hagan, et al.
The Journal of Chemical Physics
|
February 14, 2006
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
D I Doughan, L M Raff, M G Rockley, et al.
Page
of 10