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.

Publications

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Agapiou S (2013) Posterior contraction rates for the Bayesian approach to linear ill-posed inverse problems in Stochastic Processes and their Applications

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Beskos A (2011) Hybrid Monte Carlo on Hilbert spaces in Stochastic Processes and their Applications

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Brett C (2013) Accuracy and stability of filters for dissipative PDEs in Physica D: Nonlinear Phenomena

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Bréhier C (2018) Weak Error Estimates for Trajectories of SPDEs Under Spectral Galerkin Discretization in Journal of Computational Mathematics

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Cano B (2013) Stiff Oscillatory Systems, Delta Jumps and White Noise in Foundations of Computational Mathematics

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Cotter S (2010) Approximation of Bayesian Inverse Problems for PDEs in SIAM Journal on Numerical Analysis

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Cotter S (2011) Variational data assimilation using targetted random walks in International Journal for Numerical Methods in Fluids