39 citations · 66 across the 5 of their papers we have counts for
5 papers
Learning Quantities of Interest from Dynamical Systems for Observation-Consistent Inversion
Steven Mattis, Kyle Robert Steffen, Troy Butler +2
Dynamical systems arise in a wide variety of mathematical models from science and engineering. A common challenge is to quantify uncertainties on model inputs (parameters) that cor…
Bayesian calibration and sensitivity analysis for a karst aquifer model using active subspaces
Mario Teixeira Parente, Daniel Bittner, Steven Mattis +2
In this article, we perform a parameter study for a recently developed karst hydrological model. The study consists of a high-dimensional Bayesian inverse problem and a global sens…
On the relation between parameters and discharge data for a lumped karst aquifer model
Daniel Bittner, Mario Teixeira Parente, Steven Mattis +2
Hydrological models of karst aquifers are often semi-distributed, and physical processes such as infiltration and spring discharge generation are described in a lumped way. Several…
Goal-oriented adaptive surrogate construction for stochastic inversion
Steven Mattis, Barbara Wohlmuth
Stochastic inverse problems are generally solved by some form of finite sampling of a space of uncertain parameters. For computationally expensive models, surrogate response surfac…
Efficient parameter estimation for a methane hydrate model with active subspaces
Mario Teixeira Parente, Steven Mattis, Shubhangi Gupta +2
Methane gas hydrates have increasingly become a topic of interest because of their potential as a future energy resource. There are significant economical and environmental risks a…