activity
20152022
most citedComputationally efficient surrogate-based optimization of coastal storm waves heights and run-ups

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

stat.AP2022

Geometrically adapted Langevin dynamics for Markov chain Monte Carlo simulations

Mariya Mamajiwala, Debasish Roy, Serge Guillas

Markov Chain Monte Carlo (MCMC) is one of the most powerful methods to sample from a given probability distribution, of which the Metropolis Adjusted Langevin Algorithm (MALA) is a…

physics.comp-ph2020

Performance analysis of Volna-OP2 -- massively parallel code for tsunami modelling

Daniel Giles, Eugene Kashdan, Dimitra M. Salmanidou +2

The software package Volna-OP2 is a robust and efficient code capable of simulating the complete life cycle of a tsunami whilst harnessing the latest High Performance Computing (HP…

stat.ME2019

Linked Gaussian Process Emulation for Systems of Computer Models using Matérn Kernels and Adaptive Design

Deyu Ming, Serge Guillas

The state-of-the-art linked Gaussian process offers a way to build analytical emulators for systems of computer models. We generalize the closed form expressions for the linked Gau…

stat.AP20191 cited

Computationally efficient surrogate-based optimization of coastal storm waves heights and run-ups

Theodoros Mathikolonis, Volker Roeber, Serge Guillas

Storm surges cause coastal inundations due to the setup of the water surface resulting from atmospheric pressure, surface winds and breaking waves. The latter is particularly diffi…

stat.CO2019

Surrogate-based Optimization using Mutual Information for Computer Experiments (optim-MICE)

Theodoros Mathikolonis, Serge Guillas

The computational burden of running a complex computer model can make optimization impractical. Gaussian Processes (GPs) are statistical surrogates (also known as emulators) that a…

stat.CO2015

Efficient spatial modelling using the SPDE approach with bivariate splines

Xiaoyu Liu, Serge Guillas, Ming-Jun Lai

Gaussian fields (GFs) are frequently used in spatial statistics for their versatility. The associated computational cost can be a bottleneck, especially in realistic applications.…