121 citations · 141 across the 5 of their papers we have counts for
5 papers
Review of ensemble gradients for robust optimisation
Patrick N. Raanes, Andreas S. Stordal, Rolf J. Lorentzen
In robust optimisation problems the objective function consists of an average over (an ensemble of) uncertain parameters. Ensemble optimisation (EnOpt) implements steepest descent…
An organ deformation model using Bayesian inference to combine population and patient-specific data
Øyvind Lunde Rørtveit, Liv Bolstad Hysing, Andreas Størksen Stordal +1
Objective: Organ deformation models have the potential to improve delivery and reduce toxicity of radiotherapy, but existing data-driven motion models are based on either patient-s…
Revising the stochastic iterative ensemble smoother
Patrick N. Raanes, Geir Evensen, Andreas S. Stordal
Ensemble randomized maximum likelihood (EnRML) is an iterative (stochastic) ensemble smoother, used for large and nonlinear inverse problems, such as history matching and data assi…
Iterative ensemble smoother as an approximate solution to a regularized minimum-average-cost problem: theory and applications
Xiaodong Luo, Andreas S. Stordal, Rolf J. Lorentzen +1
The focus of this work is on an alternative implementation of the iterative ensemble smoother (iES). We show that iteration formulae similar to those used in \cite{chen2013-levenbe…
Toward an enhanced Bayesian estimation framework for multiphase flow soft-sensing
Xiaodong Luo, Rolf J. Lorentzen, Andreas S. Stordal +1
In this work the authors study the multiphase flow soft-sensing problem based on a previously established framework. There are three functional modules in this framework, namely, a…