Publications
Anyosa, S., Eidsvik, J. and Pizarro, O. (2022). Adaptive spatial designs minimizing the integrated Bernoulli variance in spatial logistic regression models - with an application to benthic habitat mapping. Computational Statistics & Data Analysis, 107643. Paper
Berild M.O., and Fuglstad, G-A. (2023). Spatially varying anisotropy for Gaussian random fields in three-dimensional space. Spatial Statistics. Paper
Berild, M.O., Ge, Y., Eidsvik, J., Fuglstad, G.A. and Ellingsen, I. (2024). Efficient 3D real-time adaptive AUV sampling of a river plume front. Frontiers in Marine Science. Paper
Foss, K. H., Berget, G. E., & Eidsvik, J. (2021). Using an autonomous underwater vehicle with onboard stochastic advection-diffusion models to map excursion sets of environmental variables. Environmetrics, e2702. Paper
Fossum, T. O., Travelletti, C., Eidsvik, J., Ginsbourger, D., & Rajan, K. (2021). Learning excursion sets of vector-valued Gaussian random fields for autonomous ocean sampling. The Annals of Applied Statistics, 15(2), 597-618. Paper
Ge, Y., Olaisen, A.J.H., Eidsvik, J., Jain, R.P. and Johansen, T.A., (2022). Long-Horizon Informative Path Planning with Obstacles and Time Constraints. IFAC-PapersOnLine, 55(31), pp.124-129.
Ge, Y., Eidsvik, J., and Mo-Bjørkelund, T. (2023), 3-D adaptive AUV sampling for classification of water masses. IEEE Journal of Oceanic Engineering. Paper
Lie, H.S. and Eidsvik, J., 2021. Inference in cylindrical models having latent Markovian classes—With an application to ocean current data. Spatial Statistics, 41, p.100497.Paper
Rajan, K., Alvera-Azcarate, A., Eidsvik, J., and Subramaniam, A., (2023), Symposium on the Advances in Ocean Sampling. Paper