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Daniel Giles
Daniel Giles
Verified email at ucl.ac.uk
Title
Cited by
Cited by
Year
Faster than real time tsunami warning with associated hazard uncertainties
D Giles, D Gopinathan, S Guillas, F Dias
Frontiers in Earth Science 8, 560, 2021
242021
The VOLNA-OP2 tsunami code (version 1.5)
IZ Reguly, D Giles, D Gopinathan, L Quivy, JH Beck, MB Giles, S Guillas, ...
Geoscientific Model Development 11 (11), 4621-4635, 2018
232018
Performance analysis of Volna-OP2 – massively parallel code for tsunami modelling
D Giles, E Kashdan, DM Salmanidou, S Guillas, F Dias
Computers & Fluids 209, 104649, 2020
132020
Multilevel Bayesian Quadrature
K Li, D Giles, T Karvonen, S Guillas, FX Briol
International Conference on Artificial Intelligence and Statistics, 1845-1868, 2023
42023
Meteotsunamis and other anomalous “tidal surge” events in Western Europe in Summer 2022
E Renzi, C Bergin, T Kokina, DS Pelaez-Zapata, D Giles, F Dias
Physics of Fluids 35 (046605), 2023
22023
Modelling with Volna-OP2—Towards Tsunami Threat Reduction for the Irish Coastline.
D Giles, B McConnell, F Dias
Geosciences 10 (226), 2020
22020
Automated approaches for capturing localised tsunami response‐Application to the French coastlines
D Giles, A Gailler, F Dias
Journal of Geophysical Research: Oceans 127 (6), e2022JC018467, 2022
12022
ParticleDA.jl v.1.0: a distributed particle-filtering data assimilation package
D Giles, MM Graham, M Giordano, T Koskela, A Beskos, S Guillas
Geosci. Model Dev. 17, 2427–2445, 2024
2024
A Hybrid Machine Learning Climate Simulation Using High Resolution Convection Modelling
D Giles, J Briant, C Morcrette, S Guillas
SIAM Conference on Uncertainty Quantification (UQ24), 2024
2024
Time-dependent influence metric for cascade dynamics on networks
JP Gleeson, A Cassidy, D Giles, A Faqeeh
https://arxiv.org/abs/2401.16978, 2024
2024
Fusion of a Machine Learning and Climate Model to Embed High Resolution Variability into a Coarse Resolution Climate Simulation
D Giles, C Morcrette, S Guillas
SIAM Conference on Mathematical & Computational Issues in the Geosciences (GS23), 2023
2023
Development of fast computational methods for tsunami modelling
D Giles
University College Dublin. School of Mathematics and Statistics, 2021
2021
Comparison of local amplification factors for fast forecast coastal tsunami amplitude modeling based on the extended Green's law
A Gailler, D Giles
EGU General Assembly Conference Abstracts, 7412, 2020
2020
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