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 | 147 | 2012 |
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 | 68 | 2012 |
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 | 42 | 2016 |
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 | 37 | 2013 |
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 | 37 | 2013 |
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 | 36 | 2020 |
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 | 32 | 2019 |
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 | 31 | 2011 |
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 | 23 | 2013 |
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 | 16 | 2015 |
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 | 15 | 2014 |
Adaptive load balancing for massively parallel multi-level Monte Carlo solvers J Šukys International Conference on Parallel Processing and Applied Mathematics, 47-56, 2013 | 15 | 2013 |
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 | 13 | 2017 |
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 | 10 | 2016 |
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 | 6 | 2017 |
Multilevel Monte Carlo approximations of statistical solutions to the Navier-Stokes equations A Barth, J Šukys ETH-Zürich, 2013 | 5 | 2013 |
SPUX Framework: a Scalable Package for Bayesian Uncertainty Quantification and Propagation J Šukys, M Bacci arXiv preprint arXiv:2105.05969, 2021 | 4 | 2021 |
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 | 1 | 2012 |
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 |