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ORCIDKjetil Olsen Lye
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2020 – today
- 2024
[j5]Sølve Eidnes
, Kjetil Olsen Lye:
Pseudo-Hamiltonian neural networks for learning partial differential equations. J. Comput. Phys. 500: 112738 (2024)- 2023
- [i7]Sølve Eidnes, Kjetil Olsen Lye:
Pseudo-Hamiltonian neural networks for learning partial differential equations. CoRR abs/2304.14374 (2023) - 2022
- [j4]Franz G. Fuchs, Kjetil Olsen Lye, Halvor Møll Nilsen, Alexander J. Stasik, Giorgio Sartor:
Constraint Preserving Mixers for the Quantum Approximate Optimization Algorithm. Algorithms 15(6): 202 (2022) - [j3]Ulrik Skre Fjordholm, Kjetil Olsen Lye:
Convergence Rates of Monotone Schemes for Conservation Laws for Data with Unbounded Total Variation. J. Sci. Comput. 91(2): 32 (2022) - 2020
- [j2]Kjetil O. Lye, Siddhartha Mishra, Deep Ray:
Deep learning observables in computational fluid dynamics. J. Comput. Phys. 410: 109339 (2020) - [i6]Kjetil O. Lye, Siddhartha Mishra, Deep Ray, Praveen Chandrasekhar:
Iterative Surrogate Model Optimization (ISMO): An active learning algorithm for PDE constrained optimization with deep neural networks. CoRR abs/2008.05730 (2020) - [i5]Ulrik Skre Fjordholm, Kjetil Olsen Lye:
Convergence rates of monotone schemes for conservation laws for data with unbounded total variation. CoRR abs/2010.07642 (2020)
2010 – 2019
- 2019
- [i4]Kjetil O. Lye, Siddhartha Mishra, Deep Ray:
Deep learning observables in computational fluid dynamics. CoRR abs/1903.03040 (2019) - [i3]Ulrik Skre Fjordholm, Kjetil O. Lye, Siddhartha Mishra, Franziska Weber:
Statistical solutions of hyperbolic systems of conservation laws: numerical approximation. CoRR abs/1906.02536 (2019) - [i2]Kjetil O. Lye, Siddhartha Mishra, Roberto Molinaro:
A Multi-level procedure for enhancing accuracy of machine learning algorithms. CoRR abs/1909.09448 (2019) - [i1]Kjetil Olsen Lye:
Alsvinn: A Fast multi-GPGPU finite volume solver with a strong emphasis on reproducibility. CoRR abs/1912.07645 (2019) - 2018
- [j1]Ulrik S. Fjordholm, Kjetil O. Lye, Siddhartha Mishra:
Numerical Approximation of Statistical Solutions of Scalar Conservation Laws. SIAM J. Numer. Anal. 56(5): 2989-3009 (2018) - 2012
- [c1]Christopher Dyken, Kjetil Olsen Lye, Johan Seland, Erik W. Bjønnes, Jon M. Hjelmervik, Jens Olav Nygaard, Trond Runar Hagen:
A framework for OpenGL client-server rendering. CloudCom 2012: 729-734
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last updated on 2024-03-11 23:30 CET by the dblp team
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