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L M Raff

Showing results (1-10 of 10) with videos related to

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The Journal of Chemical Physics|June 3, 2010
Input vector optimization of feed-forward neural networks for fitting ab initio potential-energy databasesM 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 databaseM Malshe, A Pukrittayakamee, L M Raff, et al.
The Journal of Chemical Physics|August 7, 2008
Parametrization of analytic interatomic potential functions using neural networksM Malshe, R Narulkar, L M Raff, 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 methodM 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 networksL 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 networksA 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 networksD I Doughan, L M Raff, M G Rockley, et al.
The Journal of Chemical Physics|May 20, 2009
Development of generalized potential-energy surfaces using many-body expansions, neural networks, and moiety energy approximationsM Malshe, R Narulkar, L M Raff, et al.
The Journal of Chemical Physics|September 1, 2006
Retraction: "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" [J. Chem. Phys. 124, 054321 (2006)]D I Doughan, L M Raff, M G Rockley, et al.
The Journal of Physical Chemistry. A|January 7, 2009
A self-starting method for obtaining analytic potential-energy surfaces from ab initio electronic structure calculationsP M Agrawal, M Malshe, R Narulkar, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
The Journal of Chemical Physics|June 3, 2010
Input vector optimization of feed-forward neural networks for fitting ab initio potential-energy databasesM 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 databaseM Malshe, A Pukrittayakamee, L M Raff, et al.
The Journal of Chemical Physics|August 7, 2008
Parametrization of analytic interatomic potential functions using neural networksM Malshe, R Narulkar, L M Raff, 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 methodM 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 networksL 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 networksA 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 networksD I Doughan, L M Raff, M G Rockley, et al.
The Journal of Chemical Physics|May 20, 2009
Development of generalized potential-energy surfaces using many-body expansions, neural networks, and moiety energy approximationsM Malshe, R Narulkar, L M Raff, et al.
The Journal of Chemical Physics|September 1, 2006
Retraction: "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" [J. Chem. Phys. 124, 054321 (2006)]D I Doughan, L M Raff, M G Rockley, et al.
The Journal of Physical Chemistry. A|January 7, 2009
A self-starting method for obtaining analytic potential-energy surfaces from ab initio electronic structure calculationsP M Agrawal, M Malshe, R Narulkar, et al.
Pageof 1