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Kipton Barros

Showing results (21-30 of 48) with videos related to

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Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|December 15, 2015
Physics-based statistical learning approach to mesoscopic model selectionSøren Taverniers, Terry S Haut, Kipton Barros, et al.
Physical Review. E|June 17, 2023
Flexible class of exact Hubbard-Stratonovich transformationsSeher Karakuzu, Benjamin Cohen-Stead, Cristian D Batista, et al.
Physical Review Letters|June 17, 2017
Mott Transition in a Metallic Liquid: Gutzwiller Molecular Dynamics SimulationsGia-Wei Chern, Kipton Barros, Cristian D Batista, et al.
Physical Review. E|May 20, 2022
Dynamical tuning of the chemical potential to achieve a target particle number in grand canonical Monte Carlo simulationsCole Miles, Benjamin Cohen-Stead, Owen Bradley, et al.
Physical Review Letters|November 26, 2016
Resistivity Minimum in Highly Frustrated Itinerant MagnetsZhentao Wang, Kipton Barros, Gia-Wei Chern, et al.
Physical Review. E|July 20, 2022
Fast and scalable quantum Monte Carlo simulations of electron-phonon modelsBenjamin Cohen-Stead, Owen Bradley, Cole Miles, et al.
Journal of Physics. Condensed Matter : an Institute of Physics Journal|November 17, 2020
Fast and stable deep-learning predictions of material properties for solid solution alloysMassimiliano Lupo Pasini, Ying Wai Li, Junqi Yin, et al.
The Journal of Chemical Physics|May 9, 2023
Lightweight and effective tensor sensitivity for atomistic neural networksMichael Chigaev, Justin S Smith, Steven Anaya, et al.
Journal of Chemical Theory and Computation|May 10, 2023
Semi-Empirical Shadow Molecular Dynamics: A PyTorch ImplementationMaksim Kulichenko, Kipton Barros, Nicholas Lubbers, et al.
Journal of Chemical Theory and Computation|June 17, 2020
Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and HalogensChristian Devereux, Justin S Smith, Kate K Huddleston, et al.
Pageof 5

Showing results (21-30 of 48) with videos related to

Sort By:
Pageof 5
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|December 15, 2015
Physics-based statistical learning approach to mesoscopic model selectionSøren Taverniers, Terry S Haut, Kipton Barros, et al.
Physical Review. E|June 17, 2023
Flexible class of exact Hubbard-Stratonovich transformationsSeher Karakuzu, Benjamin Cohen-Stead, Cristian D Batista, et al.
Physical Review Letters|June 17, 2017
Mott Transition in a Metallic Liquid: Gutzwiller Molecular Dynamics SimulationsGia-Wei Chern, Kipton Barros, Cristian D Batista, et al.
Physical Review. E|May 20, 2022
Dynamical tuning of the chemical potential to achieve a target particle number in grand canonical Monte Carlo simulationsCole Miles, Benjamin Cohen-Stead, Owen Bradley, et al.
Physical Review Letters|November 26, 2016
Resistivity Minimum in Highly Frustrated Itinerant MagnetsZhentao Wang, Kipton Barros, Gia-Wei Chern, et al.
Physical Review. E|July 20, 2022
Fast and scalable quantum Monte Carlo simulations of electron-phonon modelsBenjamin Cohen-Stead, Owen Bradley, Cole Miles, et al.
Journal of Physics. Condensed Matter : an Institute of Physics Journal|November 17, 2020
Fast and stable deep-learning predictions of material properties for solid solution alloysMassimiliano Lupo Pasini, Ying Wai Li, Junqi Yin, et al.
The Journal of Chemical Physics|May 9, 2023
Lightweight and effective tensor sensitivity for atomistic neural networksMichael Chigaev, Justin S Smith, Steven Anaya, et al.
Journal of Chemical Theory and Computation|May 10, 2023
Semi-Empirical Shadow Molecular Dynamics: A PyTorch ImplementationMaksim Kulichenko, Kipton Barros, Nicholas Lubbers, et al.
Journal of Chemical Theory and Computation|June 17, 2020
Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and HalogensChristian Devereux, Justin S Smith, Kate K Huddleston, et al.
Pageof 5