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Jonas Šukys
Jonas Šukys
Eawag Head of Scientific Computing Group
Verified email at eawag.ch - Homepage
Title
Cited by
Cited by
Year
Multi-level Monte Carlo finite volume methods for nonlinear systems of conservation laws in multi-dimensions
S Mishra, C Schwab, J Šukys
Journal of Computational Physics 231 (8), 3365-3388, 2012
1472012
Multilevel Monte Carlo Finite Volume Methods for Shallow Water Equations with Uncertain Topography in Multi-dimensions
S Mishra, C Schwab, J Sukys
SIAM Journal on Scientific Computing 34 (6), B761-B784, 2012
682012
Multi-Level Monte Carlo Finite Volume methods for uncertainty quantification of acoustic wave propagation in random heterogeneous layered medium
S Mishra, C Schwab, J Šukys
Journal of Computational Physics 312, 192-217, 2016
422016
Multi-level Monte Carlo finite volume methods for uncertainty quantification in nonlinear systems of balance laws
S Mishra, C Schwab, J Šukys
Uncertainty quantification in computational fluid dynamics, 225-294, 2013
372013
Multi-level Monte Carlo finite volume methods for uncertainty quantification in nonlinear systems of balance laws
S Mishra, C Schwab, J Šukys
Uncertainty Quantification in Computational Fluid Dynamics, 225-294, 2013
372013
Data assimilation of in situ and satellite remote sensing data to 3D hydrodynamic lake models: a case study using Delft3D-FLOW v4. 03 and OpenDA v2. 4
T Baracchini, PY Chu, J Šukys, G Lieberherr, S Wunderle, A Wüest, ...
Geoscientific Model Development 13 (3), 1267-1284, 2020
362020
Static load balancing for multi-level Monte Carlo finite volume solvers
J Šukys, S Mishra, C Schwab
International Conference on Parallel Processing and Applied Mathematics, 245-254, 2011
312011
Computational study of the collapse of a cloud with gas bubbles in a liquid
U Rasthofer, F Wermelinger, P Karnakov, J Šukys, P Koumoutsakos
Physical Review Fluids 4 (6), 063602, 2019
302019
Multi-level Monte Carlo finite difference and finite volume methods for stochastic linear hyperbolic systems
J Šukys, S Mishra, C Schwab
Monte Carlo and Quasi-Monte Carlo Methods 2012, 649-666, 2013
232013
Multi-level Monte Carlo finite volume method for shallow water equations with uncertain parameters applied to landslides-generated tsunamis
C Sanchez-Linares, M de la Asunción, MJ Castro, S Mishra, J Šukys
Applied Mathematical Modelling 39 (23-24), 7211-7226, 2015
162015
Robust multi-level Monte Carlo finite volume methods for systems of hyperbolic conservation laws with random input data
J Šukys
Diss., Eidgenössische Technische Hochschule ETH Zürich, Nr. 21990, 2014, 2014
152014
Adaptive load balancing for massively parallel multi-level Monte Carlo solvers
J Šukys
International Conference on Parallel Processing and Applied Mathematics, 47-56, 2013
152013
Optimal fidelity multi-level Monte Carlo for quantification of uncertainty in simulations of cloud cavitation collapse
J Šukys, U Rasthofer, F Wermelinger, P Hadjidoukas, P Koumoutsakos
arXiv preprint arXiv:1705.04374, 2017
112017
Multilevel Monte Carlo Simulation of Statistical Solutions to the Navier–Stokes Equations
A Barth, C Schwab, J Šukys
Monte Carlo and Quasi-Monte Carlo Methods, 209-227, 2016
102016
SPUX: Scalable Particle Markov Chain Monte Carlo for uncertainty quantification in stochastic ecological models
J Šukys, M Kattwinkel
Advance, Parallel Computing in Everywhere, edited by: Bassini, S., Danelutto …, 2017
62017
Multilevel Monte Carlo approximations of statistical solutions to the Navier-Stokes equations
A Barth, J Šukys
ETH-Zürich, 2013
52013
SPUX Framework: a Scalable Package for Bayesian Uncertainty Quantification and Propagation
J Šukys, M Bacci
arXiv preprint arXiv:2105.05969, 2021
42021
Multi-Level Monte Carlofinite volume methods for nonlinear systems of stochastic conservation laws in multi-dimensions
J Šukys
14th International Conference on Hyperbolic Problems: Theory, Numerics …, 2012
12012
Data assimilation in lake Geneva using the SPUX framework
A Safin, D Bouffard, J Runnalls, F Georgatos, E Bouillet, F Ozdemir, ...
EGU General Assembly Conference Abstracts, 19564, 2020
2020
SPUX: A new flexible method for uncertainty quantification with particle Markov Chain Monte Carlo-An application to aquatic ecology.
M Bacci, M Kattwinkel, P Reichert, J Šukys
Geophysical Research Abstracts 21, 2019
2019
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Articles 1–20