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François Gay-Balmaz

Showing results (1-10 of 11) with videos related to

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Physical Review Letters|February 2, 2013
Dynamics of elastic rods in perfect friction contactFrançois Gay-Balmaz, Vakhtang Putkaradze
Entropy (Basel, Switzerland)|December 3, 2020
A Variational Formulation of Nonequilibrium Thermodynamics for Discrete Open Systems with Mass and Heat TransferFrançois Gay-Balmaz, Hiroaki Yoshimura
Entropy (Basel, Switzerland)|December 3, 2020
From Lagrangian Mechanics to Nonequilibrium Thermodynamics: A Variational PerspectiveFrançois Gay-Balmaz, Hiroaki Yoshimura
Entropy (Basel, Switzerland)|December 8, 2020
Lie Group Cohomology and (Multi)Symplectic Integrators: New Geometric Tools for Lie Group Machine Learning Based on Souriau Geometric Statistical MechanicsFrédéric Barbaresco, François Gay-Balmaz
Journal of Nonlinear Science|July 5, 2024
Complex Fluid Models of Mixed Quantum-Classical DynamicsFrançois Gay-Balmaz, Cesare Tronci
Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences|August 13, 2023
Systems, variational principles and interconnections in non-equilibrium thermodynamicsFrançois Gay-Balmaz, Hiroaki Yoshimura
Journal of Nonlinear Science|May 18, 2018
Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid FlowsFrançois Gay-Balmaz, Darryl D Holm
Neural Networks : the Official Journal of the International Neural Network Society|May 9, 2025
CLPNets: Coupled Lie-Poisson neural networks for multi-part Hamiltonian systems with symmetriesChristopher Eldred, François Gay-Balmaz, Vakhtang Putkaradze
Proceedings. Mathematical, Physical, and Engineering Sciences|October 16, 2019
Koopman wavefunctions and classical-quantum correlation dynamicsDenys I Bondar, François Gay-Balmaz, Cesare Tronci
Neural Networks : the Official Journal of the International Neural Network Society|February 9, 2024
Lie-Poisson Neural Networks (LPNets): Data-based computing of Hamiltonian systems with symmetriesChristopher Eldred, François Gay-Balmaz, Sofiia Huraka, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
Physical Review Letters|February 2, 2013
Dynamics of elastic rods in perfect friction contactFrançois Gay-Balmaz, Vakhtang Putkaradze
Entropy (Basel, Switzerland)|December 3, 2020
A Variational Formulation of Nonequilibrium Thermodynamics for Discrete Open Systems with Mass and Heat TransferFrançois Gay-Balmaz, Hiroaki Yoshimura
Entropy (Basel, Switzerland)|December 3, 2020
From Lagrangian Mechanics to Nonequilibrium Thermodynamics: A Variational PerspectiveFrançois Gay-Balmaz, Hiroaki Yoshimura
Entropy (Basel, Switzerland)|December 8, 2020
Lie Group Cohomology and (Multi)Symplectic Integrators: New Geometric Tools for Lie Group Machine Learning Based on Souriau Geometric Statistical MechanicsFrédéric Barbaresco, François Gay-Balmaz
Journal of Nonlinear Science|July 5, 2024
Complex Fluid Models of Mixed Quantum-Classical DynamicsFrançois Gay-Balmaz, Cesare Tronci
Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences|August 13, 2023
Systems, variational principles and interconnections in non-equilibrium thermodynamicsFrançois Gay-Balmaz, Hiroaki Yoshimura
Journal of Nonlinear Science|May 18, 2018
Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid FlowsFrançois Gay-Balmaz, Darryl D Holm
Neural Networks : the Official Journal of the International Neural Network Society|May 9, 2025
CLPNets: Coupled Lie-Poisson neural networks for multi-part Hamiltonian systems with symmetriesChristopher Eldred, François Gay-Balmaz, Vakhtang Putkaradze
Proceedings. Mathematical, Physical, and Engineering Sciences|October 16, 2019
Koopman wavefunctions and classical-quantum correlation dynamicsDenys I Bondar, François Gay-Balmaz, Cesare Tronci
Neural Networks : the Official Journal of the International Neural Network Society|February 9, 2024
Lie-Poisson Neural Networks (LPNets): Data-based computing of Hamiltonian systems with symmetriesChristopher Eldred, François Gay-Balmaz, Sofiia Huraka, et al.
Pageof 2