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Ionut-Gabriel Farcas
Ionut-Gabriel Farcas
Postdoctoral Associate, Oden Institute for Computational Engineering and Sciences, UT Austin
Verified email at austin.utexas.edu
Title
Cited by
Cited by
Year
Reduced operator inference for nonlinear partial differential equations
E Qian, IG Farcas, K Willcox
SIAM Journal on Scientific Computing 44 (4), A1934-A1959, 2022
322022
Sensitivity-driven adaptive sparse stochastic approximations in plasma microinstability analysis
IG Farcaş, T Görler, HJ Bungartz, F Jenko, T Neckel
Journal of Computational Physics 410, 109394, 2020
172020
Data-driven low-fidelity models for multi-fidelity Monte Carlo sampling in plasma micro-turbulence analysis
J Konrad, IG Farcaş, B Peherstorfer, A Di Siena, F Jenko, T Neckel, ...
Journal of Computational Physics 451, 110898, 2022
152022
Multilevel Adaptive Sparse Leja Approximations for Bayesian Inverse Problems
IG Farcas, J Latz, E Ullmann, T Neckel, HJ Bungartz
SIAM Journal on Scientific Computing 42 (1), A424–A451, 2020
132020
Context-aware model hierarchies for higher-dimensional uncertainty quantification
IG Farcas
Technische Universität München, 2020
132020
Multilevel adaptive stochastic collocation with dimensionality reduction
IG Farcaş, PC Sârbu, HJ Bungartz, T Neckel, B Uekermann
Sparse Grids and Applications-Miami 2016, 43-68, 2018
122018
On filtering in non-intrusive data-driven reduced-order modeling
I Farcas, R Munipalli, KE Willcox
AIAA AVIATION 2022 Forum, 3487, 2022
112022
Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification
IG Farcaș, B Peherstorfer, T Neckel, F Jenko, HJ Bungartz
Computer Methods in Applied Mechanics and Engineering 406, 115908, 2023
82023
Nonintrusive uncertainty analysis of fluid-structure interaction with spatially adaptive sparse grids and polynomial chaos expansion
IG Farcaș, B Uekermann, T Neckel, HJ Bungartz
SIAM Journal on Scientific Computing 40 (2), B457-B482, 2018
82018
A general framework for quantifying uncertainty at scale
IG Farcaş, G Merlo, F Jenko
Communications Engineering 1 (1), 43, 2022
72022
Turbulence suppression by energetic particles: a sensitivity-driven dimension-adaptive sparse grid framework for discharge optimization
IG Farcaş, A Di Siena, F Jenko
Nuclear Fusion 61 (5), 056004, 2021
72021
E-health decision support system for differential diagnosis
R Cucu, C Avram, A Astilean, IG Fărcaş, J Machado
2014 IEEE International Conference on Automation, Quality and Testing …, 2014
62014
Parametric non-intrusive reduced-order models via operator inference for large-scale rotating detonation engine simulations
I Farcas, R Gundevia, R Munipalli, KE Willcox
AIAA SCITECH 2023 Forum, 0172, 2023
52023
High Dimensional Uncertainty Quantification of Fluid-Structure Interaction
IG Farcas
32015
Turbulence suppression by energetic particles: A theoretical framework for discharge optimization
IG Farcas, A Di Siena, F Jenko
arXiv e-prints, arXiv: 2101.03636, 2021
12021
Learning physics-based reduced models from data for the Hasegawa-Wakatani equations
C Gahr, IG Farcas, F Jenko
arXiv preprint arXiv:2401.05972, 2024
2024
Improving the accuracy and scalability of large-scale physics-based data-driven reduced modeling via domain decomposition
IG Farcas, RP Gundevia, R Munipalli, KE Willcox
arXiv preprint arXiv:2311.00883, 2023
2023
Comparison of numerical methods in uncertainty quantification
IG Farcas
Gesellschaft für Informatik eV, 2014
2014
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Articles 1–18