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Kjetil Olsen Lye
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Deep learning observables in computational fluid dynamics
KO Lye, S Mishra, D Ray
Journal of Computational Physics 410, 109339, 2020
1902020
Iterative surrogate model optimization (ISMO): An active learning algorithm for PDE constrained optimization with deep neural networks
KO Lye, S Mishra, D Ray, P Chandrashekar
Computer Methods in Applied Mechanics and Engineering 374, 113575, 2021
842021
Constraint preserving mixers for the quantum approximate optimization algorithm
FG Fuchs, KO Lye, H Møll Nilsen, AJ Stasik, G Sartor
Algorithms 15 (6), 202, 2022
472022
A multi-level procedure for enhancing accuracy of machine learning algorithms
KO Lye, S Mishra, R Molinaro
European Journal of Applied Mathematics 32 (3), 436-469, 2021
402021
Statistical solutions of hyperbolic systems of conservation laws: numerical approximation
US Fjordholm, K Lye, S Mishra, F Weber
Mathematical Models and Methods in Applied Sciences 30 (03), 539-609, 2020
322020
Deep Ray, and Praveen Chandrashekar. Iterative surrogate model optimization (ismo): An active learning algorithm for pde constrained optimization with deep neural networks
KO Lye, S Mishra
Computer Methods in Applied Mechanics and Engineering 374 (113575), 02, 2021
182021
Numerical approximation of statistical solutions of scalar conservation laws
US Fjordholm, K Lye, S Mishra
SIAM Journal on Numerical Analysis 56 (5), 2989-3009, 2018
162018
Pseudo-Hamiltonian neural networks for learning partial differential equations
S Eidnes, KO Lye
Journal of Computational Physics 500, 112738, 2024
132024
A framework for OpenGL client-server rendering
C Dyken, KO Lye, J Seland, EW Bjønnes, J Hjelmervik, JO Nygaard, ...
4th IEEE International Conference on Cloud Computing Technology and Science …, 2012
122012
Computation of statistical solutions of hyperbolic systems of conservation laws
KO Lye
ETH Zurich, 2020
112020
Multilevel Monte-Carlo for measure valued solutions
KO Lye
arXiv preprint arXiv:1611.07732, 2016
82016
Convergence rates of monotone schemes for conservation laws for data with unbounded total variation
US Fjordholm, KO Lye
Journal of Scientific Computing 91 (2), 32, 2022
32022
Constrained mixers for QAOA
FG Fuchs, KO Lye, HM Nilsen, AJ Stasik, G Sartor
arXiv preprint arXiv:2203.06095, 2022
32022
Alsvinn: A Fast multi-GPGPU finite volume solver with a strong emphasis on reproducibility
K Lye
arXiv preprint arXiv:1912.07645, 2019
22019
On C*-algebras related to the Roe algebra
KO Lye
22011
Multifidelity multilevel Monte Carlo method for rapid uncertainty quantification in CO2 storage applications
F Watson, Ø Klemetsdal, KO Lye
ECMOR 2024 2024 (1), 1-12, 2024
12024
Multi-level data assimilation for simplified ocean models
F Beiser, HH Holm, KO Lye, J Eidsvik
Nonlinear Processes in Geophysics Discussions 2024, 1-33, 2024
12024
Density-consistent initialization of SPH on a regular Cartesian grid: Comparative numerical study of 10 smoothing kernels in 1, 2 and 3 dimensions
A Lavrov, P Skjetne, B Lund, E Bjønnes, FO Bjørnson, JO Busklein, ...
Procedia IUTAM 18, 85-95, 2015
12015
A Comparison of DILU And ILU (0) as GPU-Accelerated Preconditioners
TM Andersen, J Torben, KO Lye, AF Rasmussen, KA Lie
SPE Reservoir Simulation Conference, D021S009R004, 2025
2025
Multi-level data assimilation for ocean forecasting using the shallow-water equations
F Beiser, HH Holm, KO Lye, J Eidsvik
Journal of Computational Physics 524, 113722, 2025
2025
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