62 citations · 126 across the 13 of their papers we have counts for
14 papers
Multilevel Bayesian Quadrature
Kaiyu Li, Daniel Giles, Toni Karvonen +2
Multilevel Monte Carlo is a key tool for approximating integrals involving expensive scientific models. The idea is to use approximations of the integrand to construct an estimator…
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…
Deep Gaussian Process Emulation using Stochastic Imputation
Deyu Ming, Daniel Williamson, Serge Guillas
Deep Gaussian processes (DGPs) provide a rich class of models that can better represent functions with varying regimes or sharp changes, compared to conventional GPs. In this work,…
An adaptive strategy for sequential designs of multilevel computer experiments
Ayao Ehara, Serge Guillas
Investigating uncertainties in computer simulations can be prohibitive in terms of computational costs, since the simulator needs to be run over a large number of input values. Bui…
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…
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…
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…
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…
Quantifying Uncertainties in the 2004 Sumatra-Andaman Earthquake Source Parameters by Stochastic Inversion
Devaraj Gopinathan, Mamatha Venugopal, Debasish Roy +3
Usual inversion for earthquake source parameters from tsunami wave data incorporates subjective elements. Noisy and possibly insufficient data also results in instability and non-u…
Computer model calibration with large non-stationary spatial outputs: application to the calibration of a climate model
Kai-Lan Chang, Serge Guillas
Bayesian calibration of computer models tunes unknown input parameters by comparing outputs with observations. For model outputs that are distributed over space, this becomes compu…
Dimension reduction for Gaussian process emulation: an application to the influence of bathymetry on tsunami heights
Xiaoyu Liu, Serge Guillas
High accuracy complex computer models, or simulators, require large resources in time and memory to produce realistic results. Statistical emulators are computationally cheap appro…
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.…
Sequential Design with Mutual Information for Computer Experiments (MICE): Emulation of a Tsunami Model
Joakim Beck, Serge Guillas
Computer simulators can be computationally intensive to run over a large number of input values, as required for optimization and various uncertainty quantification tasks. The stan…
Statistical emulation of a tsunami model for sensitivity analysis and uncertainty quantification
A. Sarri, S. Guillas, F. Dias
Due to the catastrophic consequences of tsunamis, early warnings need to be issued quickly in order to mitigate the hazard. Additionally, there is a need to represent the uncertain…