3 papers
stat.CO2022
Efficient forecasting and uncertainty quantification for large scale account level Monte Carlo models of debt recovery
Sam Baynes, Simon Cotter, Paul Russell +2
We consider the problem of forecasting debt recovery from large portfolios of non-performing unsecured consumer loans under management. The state of the art in industry is to use s…
stat.CO2019
Transport map accelerated adaptive importance sampling, and application to inverse problems arising from multiscale stochastic reaction networks
Simon L. Cotter, Ioannis G. Kevrekidis, Paul Russell
In many applications, Bayesian inverse problems can give rise to probability distributions which contain complexities due to the Hessian varying greatly across parameter space. Thi…
math.NA2015
Ensemble Transport Adaptive Importance Sampling
Colin Cotter, Simon Cotter, Paul Russell
Markov chain Monte Carlo methods are a powerful and commonly used family of numerical methods for sampling from complex probability distributions. As applications of these methods…