51 citations · 114 across the 8 of their papers we have counts for
5 papers · 1 filter
Comparison of Ensemble-Based Data Assimilation Methods for Sparse Oceanographic Data
Florian Beiser, Håvard Heitlo Holm, Jo Eidsvik
For oceanographic applications, probabilistic forecasts typically have to deal with i) high-dimensional complex models, and ii) very sparse spatial observations. In search-and-resc…
Learning excursion sets of vector-valued Gaussian random fields for autonomous ocean sampling
Trygve Olav Fossum, Cédric Travelletti, Jo Eidsvik +2
Improving and optimizing oceanographic sampling is a crucial task for marine science and maritime resource management. Faced with limited resources in understanding processes in th…
Data Assimilation for a Geological Process Model Using the Ensemble Kalman Filter
Jacob Skauvold, Jo Eidsvik
We consider the problem of conditioning a geological process-based computer simulation, which produces basin models by simulating transport and deposition of sediments, to data. Em…
A class of covariate-dependent spatiotemporal covariance functions for the analysis of daily ozone concentration
Brian J. Reich, Jo Eidsvik, Michele Guindani +2
In geostatistics, it is common to model spatially distributed phenomena through an underlying stationary and isotropic spatial process. However, these assumptions are often untenab…
Dynamic Decision Making for Graphical Models Applied to Oil Exploration
Gabriele Martinelli, Jo Eidsvik, Ragnar Hauge
This paper has been withdrawn by the authors. We present a framework for sequential decision making in problems described by graphical models. The setting is given by dependent dis…