Problems at the Applied Mathematics / Statistics Interface
Lead Research Organisation:
University of Warwick
Department Name: Mathematics
Abstract
Mathematics is the language of science, and applied mathematics is concerned with developing models with predictive capability, and with probing those models to obtain qualitative and quantitative insight into the phenomena being modelled. Statistics is data-driven and is aimed at the development of methodologies to optimize the information derived from data. The increasing complexity of phenomena that scientists and engineers wish to model, together with our increased ability to gather, store and interrogate data, mean that the subjects of applied mathematics and statistics are increasingly required to work in conjunction in order to significantly progress understanding.The research will facilitate the development of research at the interface between applied mathematics and statistics, both by the study of fundamental theoretical questions, and by their application to problems of importance in science and technology, such as chemical reactions and weather prediction.The work will thus make fundamental progress on theoretical research questions in mathematics and statistics, and will have direct application in a range of applications from the physical sciences and beyond.
Organisations
People |
ORCID iD |
Andrew Stuart (Principal Investigator) |
Publications
Bréhier C
(2018)
Weak Error Estimates for Trajectories of SPDEs Under Spectral Galerkin Discretization
in Journal of Computational Mathematics
Beskos A
(2013)
Optimal tuning of the hybrid Monte Carlo algorithm
in Bernoulli
Iglesias M
(2013)
Evaluation of Gaussian approximations for data assimilation in reservoir models
in Computational Geosciences
Pokern Y
(2013)
Posterior consistency via precision operators for Bayesian nonparametric drift estimation in SDEs
in Stochastic Processes and their Applications
Agapiou S
(2013)
Posterior contraction rates for the Bayesian approach to linear ill-posed inverse problems
in Stochastic Processes and their Applications
Iglesias M
(2013)
Ensemble Kalman methods for inverse problems
in Inverse Problems
Brett C
(2013)
Accuracy and stability of filters for dissipative PDEs
in Physica D: Nonlinear Phenomena
Blömker D
(2013)
Accuracy and stability of the continuous-time 3DVAR filter for the Navier-Stokes equation
in Nonlinearity
Hoang V
(2013)
Complexity analysis of accelerated MCMC methods for Bayesian inversion
in Inverse Problems
Dashti M
(2013)
MAP estimators and their consistency in Bayesian nonparametric inverse problems
in Inverse Problems