| Dissipative numerical schemes on Riemannian manifolds with applications to gradient flows E Celledoni, S Eidnes, B Owren, T Ringholm SIAM Journal on Scientific Computing 40 (6), A3789-A3806, 2018 | 23* | 2018 |
| Linearly implicit structure-preserving schemes for Hamiltonian systems S Eidnes, L Li, S Sato Journal of Computational and Applied Mathematics 387, 112489, 2021 | 22 | 2021 |
| Linearly implicit local and global energy-preserving methods for PDEs with a cubic Hamiltonian S Eidnes, L Li SIAM Journal on Scientific Computing 42 (5), A2865-A2888, 2020 | 18 | 2020 |
| Energy-preserving methods on Riemannian manifolds E Celledoni, S Eidnes, B Owren, T Ringholm Mathematics of Computation 89 (322), 699-716, 2020 | 16 | 2020 |
| Adaptive energy preserving methods for partial differential equations S Eidnes, B Owren, T Ringholm Advances in Computational Mathematics 44, 815-839, 2018 | 14 | 2018 |
| Order theory for discrete gradient methods S Eidnes BIT Numerical Mathematics 62 (4), 1207-1255, 2022 | 12 | 2022 |
| Shape analysis on homogeneous spaces: a generalised SRVT framework E Celledoni, S Eidnes, A Schmeding Computation and Combinatorics in Dynamics, Stochastics and Control: The Abel …, 2018 | 12* | 2018 |
| Pseudo-Hamiltonian neural networks with state-dependent external forces S Eidnes, AJ Stasik, C Sterud, E Bøhn, S Riemer-Sørensen Physica D: Nonlinear Phenomena 446, 133673, 2023 | 11* | 2023 |
| Shape analysis on Lie groups and homogeneous spaces E Celledoni, S Eidnes, M Eslitzbichler, A Schmeding Geometric Science of Information: Third International Conference, GSI 2017 …, 2017 | 9 | 2017 |
| Pseudo-Hamiltonian neural networks for learning partial differential equations S Eidnes, KO Lye Journal of Computational Physics 500, 112738, 2024 | 5 | 2024 |
| Pseudo-Hamiltonian system identification S Holmsen, S Eidnes, S Riemer-Sørensen arXiv preprint arXiv:2305.06920, 2023 | 2 | 2023 |
| Learning dynamical systems from noisy data with inverse-explicit integrators H Noren, S Eidnes, E Celledoni arXiv preprint arXiv:2306.03548, 2023 | 1 | 2023 |
| Data quality issues for vibration sensors: a case study in ferrosilicon production M Waszak, T Moen, S Eidnes, A Stasik, A Hansen, G Bouquet, A Pultier, ... Proceedings of the 2nd International Workshop on Software Engineering and AI …, 2022 | 1 | 2022 |
| Application of Optimization Algorithm on Parameters of an Empirical VIV Prediction Tool D Yin, J Wu, H Lie, J Jin, E Passano, S Sævik, S Eidnes, G Grytoyr, ... International Conference on Offshore Mechanics and Arctic Engineering 85925 …, 2022 | 1 | 2022 |
| A Hybrid Digital Twin for Optimal Si-Production K Linnestad, K Hildal, LK Jakobsson, S Eidnes, V Tjessem, EL Bjørnstad, ... Proceedings of the Silicon for the Chemical & Solar Industry XVI, 2022 | 1 | 2022 |
| Integral preserving numerical methods on moving grids S Eidnes Institutt for matematiske fag, 2013 | 1 | 2013 |
| Recency-Weighted Temporally-Segmented Ensemble for Time-Series Modeling PV Johnsen, E Bøhn, S Eidnes, F Remonato, S Riemer-Sørensen arXiv preprint arXiv:2403.02150, 2024 | | 2024 |
| Derivative-free discrete gradient methods HN Myhr, S Eidnes Journal of Computational Dynamics, 0-0, 2024 | | 2024 |
| Analysis of full-scale riser responses in field conditions based on Gaussian mixture model J Wu, S Eidnes, J Jin, H Lie, D Yin, E Passano, S Sævik, ... Journal of Fluids and Structures 116, 103793, 2023 | | 2023 |
| Numerical integrators for learning dynamical systems from noisy data H Noren, S Eidnes, E Celledoni The Symbiosis of Deep Learning and Differential Equations II, 2022 | | 2022 |
Elena CelledoniProfessor of mathematics at the Norwegian University of Science and TechnologyDirección de correo verificada de math.ntnu.no
