Combining range and intensity data with a hidden Markov model. - Ragnar Bang Huseby; Gutorm Thomas Hogasen; Geir Storvik; Kjersti Aas (ICPR (2), 1992)

A Bayesian Approach to Dynamic Contours Through Stochastic Sampling and Simulated Annealing. - Geir Storvik (IEEE Trans. Pattern Anal. Mach. Intell., 1994)

Segmentation of brain parenchyma and cerebrospinal fluid in multispectral magnetic resonance images. - Arvid Lundervold; Geir Storvik (IEEE Trans. Medical Imaging, 1995)

Automatic detection of oil spills in ERS SAR images. - Anne H. Schistad Solberg; Geir Storvik; Rune Solberg; Espen Volden (IEEE Trans. Geosci. Remote. Sens., 1999)

Lagrangian-based methods for finding MAP solutions for MRF models. - Geir Storvik; Geir Dahl (IEEE Trans. Image Process., 2000)

Deterministic and Stochastic Particle Filters in State-Space Models. - Erik Bølviken; Geir Storvik (Sequential Monte Carlo Methods in Practice, 2001)

A comparison of criteria for decision fusion and parameter estimation in statistical multisensor image classification. - Anne H. Schistad Solberg; Geir Storvik; Roger Fjørtoft (IGARSS, 2002)

Large-Scale Integer Programs in Image Analysis. - Geir Dahl; Geir Storvik; Alice Fadnes (Oper. Res., 2002)

Particle filters for state-space models with the presence of unknown static parameters. - Geir Storvik (IEEE Trans. Signal Process., 2002)

Parameter estimation and classification of multiscale remote sensing data. - Geir Storvik; Roger Fjørtoft; Anne H. Schistad Solberg (IGARSS, 2003)

Joint distributions for correlated radar images. - Bard Storvik; Geir Storvik; Roger Fjørtoft (IGARSS, 2003)

A bayesian approach to classification of multiresolution remote sensing data. - Geir Storvik; Roger Fjørtoft; Anne H. Schistad Solberg (IEEE Trans. Geosci. Remote. Sens., 2005)

On the Combination of Multisensor Data Using Meta-Gaussian Distributions. - Bard Storvik; Geir Storvik; Roger Fjørtoft (IEEE Trans. Geosci. Remote. Sens., 2009)

Coordinates and intervals in graph-based reference genomes. - Knut D. Rand; Ivar Grytten; Alexander Johan Nederbragt; Geir Storvik; Ingrid Kristine Glad; Geir Kjetil Sandve (BMC Bioinform., 2017)

Mode jumping MCMC for Bayesian variable selection in GLMM. - Aliaksandr Hubin; Geir Storvik (Comput. Stat. Data Anal., 2018)

Combining Model and Parameter Uncertainty in Bayesian Neural Networks. - Aliaksandr Hubin; Geir Storvik (CoRR, 2019)

Graph Peak Caller: Calling ChIP-seq peaks on graph-based reference genomes. - Ivar Grytten; Knut D. Rand; Alexander Johan Nederbragt; Geir Storvik; Ingrid Kristine Glad; Geir Kjetil Sandve (PLoS Comput. Biol., 2019)

Flexible Bayesian Nonlinear Model Configuration. - Aliaksandr Hubin; Geir Storvik; Florian Frommlet (J. Artif. Intell. Res., 2021)

A subsampling approach for Bayesian model selection. - Jon Lachmann; Geir Storvik; Florian Frommlet; Aliaksandr Hubin (Int. J. Approx. Reason., 2022)

Variational Inference for Bayesian Neural Networks under Model and Parameter Uncertainty. - Aliaksandr Hubin; Geir Storvik (CoRR, 2023)

Sparsifying Bayesian neural networks with latent binary variables and normalizing flows. - Lars Skaaret-Lund; Geir Storvik; Aliaksandr Hubin (Trans. Mach. Learn. Res., 2024)