These lecture notes highlight the mathematical and computational structure relating to the
formulation of, and development of algorithms for, the Bayesian approach to inverse …

This accessible research monograph investigates how'finite-dimensional'sets can be
embedded into finite-dimensional Euclidean spaces. The first part brings together a number …

We consider the inverse problem of estimating an unknown function u from noisy
measurements y of a known, possibly nonlinear, map $\mathcal {G} $ applied to u. We adopt …

This book offers an introduction to the theory of non-autonomous and stochastic dynamical
systems, with a focus on the importance of the theory in the Applied Sciences. It starts by …

A wildfire model is formulated based on balance equations for energy and fuel, where the
fuel loss due to combustion corresponds to the fuel reaction rate. The resulting coupled …

The Hybrid Monte Carlo (HMC) algorithm provides a framework for sampling from complex,
high-dimensional target distributions. In contrast with standard Markov chain Monte Carlo …

We prove the existence of a compact global attractor for the dynamics of the forced critical
surface quasi-geostrophic equation (SQG) and prove that it has finite fractal (box-counting) …

The authors investigate the long-term dynamics of the three-dimensional Navier-Stokes-
Voight model of viscoelastic incompressible fluid. Specifically, upper bounds for the number …

Motivated by recent progress in data assimilation, we develop an algorithm to dynamically
learn the parameters of a chaotic system from partial observations. Under reasonable …

In this paper mesoscopic (individual based) and macroscopic (population based) models for
mesenchymal motion of cells in fibre networks are developed. Mesenchymal motion is a …