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Søren Taverniers
Søren Taverniers
Future Concepts Division, SRI International
Verified email at sri.com
Title
Cited by
Cited by
Year
Ginns: Graph-informed neural networks for multiscale physics
EJ Hall, S Taverniers, MA Katsoulakis, DM Tartakovsky
Journal of Computational Physics 433, 110192, 2021
292021
Estimation of distributions via multilevel Monte Carlo with stratified sampling
S Taverniers, DM Tartakovsky
Journal of Computational Physics 419, 109572, 2020
272020
Accelerated multilevel Monte Carlo with kernel‐based smoothing and Latinized stratification
S Taverniers, SBM Bosma, DM Tartakovsky
Water resources research 56 (9), e2019WR026984, 2020
162020
Noise propagation in hybrid models of nonlinear systems: The Ginzburg–Landau equation
S Taverniers, FJ Alexander, DM Tartakovsky
Journal of Computational Physics 262, 313-324, 2014
162014
Mutual information for explainable deep learning of multiscale systems
S Taverniers, EJ Hall, MA Katsoulakis, DM Tartakovsky
Journal of Computational Physics 444, 110551, 2021
132021
2D particle-in-cell modeling of dielectric insulator breakdown
S Taverniers, CH Lim, JP Verboncoeur
2009 IEEE International Conference on Plasma Science-Abstracts, 1-1, 2009
112009
Conservative tightly-coupled simulations of stochastic multiscale systems
S Taverniers, AY Pigarov, DM Tartakovsky
Journal of Computational Physics 313, 400-414, 2016
102016
Physics-based statistical learning approach to mesoscopic model selection
S Taverniers, TS Haut, K Barros, FJ Alexander, T Lookman
Physical Review E 92 (5), 053301, 2015
92015
A tightly-coupled domain-decomposition approach for highly nonlinear stochastic multiphysics systems
S Taverniers, DM Tartakovsky
Journal of Computational Physics 330, 884-901, 2017
82017
Two-way coupled Cloud-In-Cell modeling of non-isothermal particle-laden flows: A Subgrid Particle-Averaged Reynolds Stress-Equivalent (SPARSE) formulation
S Taverniers, HS Udaykumar, GB Jacobs
Journal of computational physics 390, 595-618, 2019
62019
Impact of parametric uncertainty on estimation of the energy deposition into an irradiated brain tumor
S Taverniers, DM Tartakovsky
Journal of Computational Physics 348, 139-150, 2017
42017
A localized artificial diffusivity approach inspired by TVD schemes and its consistent application to compressible flows
S Mirjalili, S Taverniers, H Collis, M Behandish, A Mani
Center for Turbulence Research, Stanford University, 169-182, 2021
22021
Inverse asymptotic treatment: capturing discontinuities in fluid flows via equation modification
S Mirjalili, S Taverniers, H Collis, M Behandish, A Mani
Journal of Computational Science 73, 102141, 2023
12023
Accelerating Part-Scale Simulation in Liquid Metal Jet Additive Manufacturing via Operator Learning
S Taverniers, S Korneev, KM Pietrzyk, M Behandish
arXiv preprint arXiv:2202.03665, 2022
12022
Graph-informed neural networks
S Taverniers, EJ Hall, MA Katsoulakis, DM Tartakovsky
AAAI 2021 Spring Symposium Series: Combining Artificial Intelligence and …, 2021
12021
Machine-learning based multi-scale model for shock-particle interactions
O Sen, S Taverniers, P Das, G Jacobs, HS Udaykumar
Bulletin of the American Physical Society 64, 2019
12019
Multi-scale Simulation of the Interaction of a Shock Wave and a Cloud of Particles
S Taverniers, GB Jacobs, V Fountoulakis, O Sen, HS Udaykumar
31st International Symposium on Shock Waves 2: Applications 31, 467-473, 2019
12019
Surrogate modeling of molten droplet coalescence in additive manufacturing
S Taverniers, M Behandish, S Korneev
US Patent App. 17/864,082, 2024
2024
A multi-physics compiler for generating numerical solvers from differential equations
JT Maxwell III, M Behandish, S Taverniers
arXiv preprint arXiv:2311.16404, 2023
2023
A finite element method to compute the damping rate of oscillating fluids inside microfluidic nozzles
S Taverniers, S Korneev, C Somarakis, AJ Lew
arXiv preprint arXiv:2307.00094, 2023
2023
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Articles 1–20