no code implementations • 13 Sep 2023 • Antonio Malpica-Morales, Peter Yatsyshin, Miguel A. Duran-Olivencia, Serafim Kalliadasis
We combine a Bayesian inference approach with the classical DFT apparatus to reconstruct the external potential, yielding a probabilistic description of the external potential functional form with inherent uncertainty quantification.
no code implementations • 7 Oct 2020 • Peter Yatsyshin, Serafim Kalliadasis, Andrew B. Duncan
In our case, the output of the learning algorithm is a probability distribution over a family of free energy functionals, consistent with the observed particle data.
no code implementations • 21 Jul 2020 • José A. Carrillo, Serafim Kalliadasis, Fuyue Liang, Sergio P. Perez
We then compare the prediction accuracy of the neural network with and without applying the Cahn-Hilliard filter to the damaged images test.
1 code implementation • 3 Dec 2018 • José A. Carrillo, Serafim Kalliadasis, Sergio P. Perez, Chi-Wang Shu
Well balanced and free energy dissipative first- and second-order accurate finite volume schemes are proposed for a general class of hydrodynamic systems with linear and nonlinear damping.
Numerical Analysis Statistical Mechanics Applied Physics Computational Physics Fluid Dynamics 35Lxx, 65Yxx, 65Zxx, 82Bxx, 82Dxx