5 citations · 5 across the 2 of their papers we have counts for
4 papers
Invariant Image Reparameterisation: Bridging Symbolic and Numerical Methods for Identifiability Analysis, Model Reduction, and Prediction
Oliver J. Maclaren, Ruanui Nicholson, Joel A. Trent +2
Structural and practical parameter non-identifiability issues are common when mathematical models are used to interpret data. Such issues motivate model reparameterisation and redu…
Beyond Independence: on Jointly Normal Priors in Bayesian Inversion
Ruanui Nicholson, Matti Niskanen, Oliver J. Maclaren +1
We consider joint inversion for two or more unknown parameters from observational data in the Bayesian framework. Standard approaches often either treat the parameters as independe…
Ensemble Kalman Inversion for Geothermal Reservoir Modelling
Alex de Beer, Elvar K Bjarkason, Michael Gravatt +4
Numerical models of geothermal reservoirs typically depend on hundreds or thousands of unknown parameters, which must be estimated using sparse, noisy data. However, these models c…
Data Space Inversion for Efficient Predictions and Uncertainty Quantification for Geothermal Models
Alex de Beer, Andrew Power, Daniel Wong +7
The ability to make accurate predictions with quantified uncertainty provides a crucial foundation for the successful management of a geothermal reservoir. Conventional approaches…