activity
20182026
most citedDiagnostic-Driven Nonstationary Emulators Using Kernel Mixtures

1 citations · 2 across the 7 of their papers we have counts for

collaborators

8 papers

math.DS2026

From trends to optimized forecasts: Quantifying the skill and advancing the utility of dynamics-based early warnings for tipping events

Franco Du Plessis, Victoria Volodina, Chris A. Boulton +5

In this paper we explore and extend the state of the art for understanding the skill and utility of early warnings of critical transitions (tipping points) in forced nonlinear syst…

stat.ME2023

Propagating moments in probabilistic graphical models with polynomial regression forms for decision support systems

Victoria Volodina, Nikki Sonenberg, Peter Challenor +1

Probabilistic graphical models are widely used to model complex systems under uncertainty. Traditionally, Gaussian directed graphical models are applied for analysis of large netwo…

stat.AP2023★ 1 cited

Using infinite server queues with partial information for occupancy prediction

Nikki Sonenberg, Victoria Volodina, Peter G. Challenor +1

Motivated by demand prediction for the custodial prison population in England and Wales, this paper describes an approach to the study of service systems using infinite server queu…

stat.AP2022

A Bayesian Decision Support System in Energy Systems Planning

Victoria Volodina, Nikki Sonenberg, Peter Challenor +1

Gaussian Process (GP) emulators are widely used to approximate complex computer model behaviour across the input space. Motivated by the problem of coupling computer models, recent…

stat.AP2022

Propagating uncertainty in a network of energy models

Victoria Volodina, Nikki Sonenberg, Jim Q. Smith +3

Computer models are widely used in decision support for energy systems operation, planning and policy. A system of models is often employed, where model inputs themselves arise fro…

math.ST2020

Majorisation as a theory for uncertainty

Victoria Volodina, Nikki Sonenberg, Edward Wheatcroft +1

Majorisation, also called rearrangement inequalities, yields a type of stochastic ordering in which two or more distributions can be compared. In this paper we argue that majorisat…

stat.AP2020

Comparing district heating options under uncertainty using stochastic ordering

Victoria Volodina, Edward Wheatcroft, Henry Wynn

District heating is a network of pipes through which heat is delivered from a centralised source. It is expected to play an important role in the decarbonisation of the energy sect…

stat.ME2018★ 1 cited

Diagnostic-Driven Nonstationary Emulators Using Kernel Mixtures

Victoria Volodina, Daniel B. Williamson

Weakly stationary Gaussian processes (GPs) are the principal tool in the statistical approaches to the design and analysis of computer experiments (or Uncertainty Quantification).…