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Michele Ceriotti

Showing results (1-10 of 149) with videos related to

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The Journal of Chemical Physics|April 22, 2019
Unsupervised machine learning in atomistic simulations, between predictions and understandingMichele Ceriotti
The Journal of Chemical Physics|November 30, 2019
Incorporating long-range physics in atomic-scale machine learningAndrea Grisafi, Michele Ceriotti
The Journal of Chemical Physics|January 3, 2015
Direct path integral estimators for isotope fractionation ratiosBingqing Cheng, Michele Ceriotti
The Journal of Chemical Physics|June 25, 2018
Communication: Computing the Tolman length for solid-liquid interfacesBingqing Cheng, Michele Ceriotti
The Journal of Chemical Physics|November 10, 2014
Recognizing molecular patterns by machine learning: an agnostic structural definition of the hydrogen bondPiero Gasparotto, Michele Ceriotti
The Journal of Chemical Physics|January 23, 2017
Bridging the gap between atomistic and macroscopic models of homogeneous nucleationBingqing Cheng, Michele Ceriotti
Chimia|December 30, 2019
Machine Learning at the Atomic ScaleFélix Musil, Michele Ceriotti
The Journal of Chemical Physics|January 10, 2013
Efficient methods and practical guidelines for simulating isotope effectsMichele Ceriotti, Thomas E Markland
Physical Review Letters|September 26, 2012
Efficient first-principles calculation of the quantum kinetic energy and momentum distribution of nucleiMichele Ceriotti, David E Manolopoulos
The Journal of Chemical Physics|March 17, 2018
Fine tuning classical and quantum molecular dynamics using a generalized Langevin equationMariana Rossi, Venkat Kapil, Michele Ceriotti
Pageof 15

Showing results (1-10 of 149) with videos related to

Sort By:
Pageof 15
The Journal of Chemical Physics|April 22, 2019
Unsupervised machine learning in atomistic simulations, between predictions and understandingMichele Ceriotti
The Journal of Chemical Physics|November 30, 2019
Incorporating long-range physics in atomic-scale machine learningAndrea Grisafi, Michele Ceriotti
The Journal of Chemical Physics|January 3, 2015
Direct path integral estimators for isotope fractionation ratiosBingqing Cheng, Michele Ceriotti
The Journal of Chemical Physics|June 25, 2018
Communication: Computing the Tolman length for solid-liquid interfacesBingqing Cheng, Michele Ceriotti
The Journal of Chemical Physics|November 10, 2014
Recognizing molecular patterns by machine learning: an agnostic structural definition of the hydrogen bondPiero Gasparotto, Michele Ceriotti
The Journal of Chemical Physics|January 23, 2017
Bridging the gap between atomistic and macroscopic models of homogeneous nucleationBingqing Cheng, Michele Ceriotti
Chimia|December 30, 2019
Machine Learning at the Atomic ScaleFélix Musil, Michele Ceriotti
The Journal of Chemical Physics|January 10, 2013
Efficient methods and practical guidelines for simulating isotope effectsMichele Ceriotti, Thomas E Markland
Physical Review Letters|September 26, 2012
Efficient first-principles calculation of the quantum kinetic energy and momentum distribution of nucleiMichele Ceriotti, David E Manolopoulos
The Journal of Chemical Physics|March 17, 2018
Fine tuning classical and quantum molecular dynamics using a generalized Langevin equationMariana Rossi, Venkat Kapil, Michele Ceriotti
Pageof 15