Jo Eidsvik

发表

A revised implicit equal‐weights particle filter

Jacob Skauvold, Jo Eidsvik, Peter Jan van Leeuwen, 2019, Quarterly Journal of the Royal Meteorological Society.

Dynamic decision making for graphical models applied to oil exploration

Jo Eidsvik, Gabriele Martinelli, Ragnar Hauge, 2012, Eur. J. Oper. Res..

Modeling Dependencies Between oil Exploration Prospects with Bayesian Networks

Jo Eidsvik, Ragnar Hauge, Marita Stien, 2012 .

Parameter estimation in high dimensional Gaussian distributions

Jo Eidsvik, Erlend Aune, Daniel P. Simpson, 2011, Stat. Comput..

Problems and projects

Tapan Mukerji, Debarun Bhattacharjya, Jo Eidsvik, 2015 .

Earth sciences applications

Tapan Mukerji, Debarun Bhattacharjya, Jo Eidsvik, 2015 .

Strategies for Petroleum Exploration on the Basis of Bayesian Networks: A Case Study

Jo Eidsvik, Gabriele Martinelli, Ragnar Hauge, 2014 .

Estimation and Prediction in Spatial Models With Block Composite Likelihoods

Jo Eidsvik, Brian J. Reich, Jarad Niemi, 2014 .

The Value of Information in Portfolio Problems with Dependent Projects

Tapan Mukerji, Debarun Bhattacharjya, Jo Eidsvik, 2013, Decis. Anal..

Dynamic exploration designs for graphical models using clustering with applications to petroleum exploration

Jo Eidsvik, Gabriele Martinelli, J. Eidsvik, 2014, Knowl. Based Syst..

Kalman filter variants in the closed skew normal setting

Javad Rezaie, Jo Eidsvik, J. Eidsvik, 2014, Comput. Stat. Data Anal..

The Value of Information in Spatial Decision Making

Tapan Mukerji, Debarun Bhattacharjya, Jo Eidsvik, 2010 .

Adaptive Sampling of Ocean Processes Using an AUV with a Gaussian Proxy Model

Tor Arne Johansen, Jo Eidsvik, Kanna Rajan, 2018 .

Strategies for petroleum exploration based on Bayesian Networks: a case study

Jo Eidsvik, Gabriele Martinelli, Ragnar Hauge, 2012 .

A parametric model for seismic wavelets—with estimation and uncertainty quantification

Jacob Skauvold, Jo Eidsvik, Ulrich Theune, 2016 .

Simulation–Regression Approximations for Value of Information Analysis of Geophysical Data

Tapan Mukerji, Debarun Bhattacharjya, Jo Eidsvik, 2017, Mathematical Geosciences.

Markov Chain Monte Carlo Algorithms and their Applications to Petroleum Reservoir Characterization

Jo Eidsvik, 2003 .

Sequential information gathering schemes for spatial risk and decision analysis applications

Debarun Bhattacharjya, Jo Eidsvik, Gabriele Martinelli, 2018, Stochastic Environmental Research and Risk Assessment.

selected statistical models and sampling methods

Tapan Mukerji, Debarun Bhattacharjya, Jo Eidsvik, 2015 .

Value of Information in the Earth Sciences: Integrating Spatial Modeling and Decision Analysis

Tapan Mukerji, Debarun Bhattacharjya, Jo Eidsvik, 2016 .

Statistical models and methods

Tapan Mukerji, Debarun Bhattacharjya, Jo Eidsvik, 2015 .

Value of Information Analysis for Time-lapse Seismic Data by Simulation-Regression

Tapan Mukerji, Jo Eidsvik, Geetartha Dutta, 2016 .

Value of information analysis for subsurface energy resources applications

Tapan Mukerji, Jo Eidsvik, Geetartha Dutta, 2019 .

Approximate Bayesian inference in spatial GLMM with skew normal latent variables

Jo Eidsvik, Mohsen Mohammadzadeh, Fatemeh Hosseini, 2011, Comput. Stat. Data Anal..

Directional Metropolis : Hastings Updates for Posteriors with Nonlinear Likelihoods

Haakon Tjelmeland, Jo Eidsvik, H. Tjelmeland, 2005 .

A skewed unscented Kalman filter

Javad Rezaie, Jo Eidsvik, J. Eidsvik, 2016, Int. J. Control.

Norges Teknisk-naturvitenskapelige Universitet Iterative Numerical Methods for Sampling from High Dimensional Gaussian Distributions Iterative Numerical Methods for Sampling from High Dimensional Gaussian Distributions

Jo Eidsvik, Yvo Pokern, Erlend Aune, 2022 .

Norges Teknisk-naturvitenskapelige Universitet Approximate Bayesian Inference for Large Spatial Datasets Using Predictive Process Models Approximate Bayesian Inference for Large Spatial Datasets Using Predictive Process Models

Andrew O. Finley, Jo Eidsvik, Håvard Rue, 2022 .

Value of Information Analysis for Complex Simulator Models: Application to Wind Farm Maintenance

Iver Bakken Sperstad, Debarun Bhattacharjya, Jo Eidsvik, 2020, Decis. Anal..

On directional Metropolis–Hastings algorithms

Jo Eidsvik, Håkon Tjelmeland, H. Tjelmeland, 2006, Stat. Comput..

A Gaussian mixture Monte Carlo filter for state estimation in very high dimensional nonlinear systems

Javad Rezaie, Jo Eidsvik, 2012 .

Compact models for adaptive sampling in marine robotics

Martin Ludvigsen, Jo Eidsvik, Thom Maughan, 2020, Int. J. Robotics Res..

Toward adaptive robotic sampling of phytoplankton in the coastal ocean

Martin Ludvigsen, Jo Eidsvik, Geir Johnsen, 2019, Science Robotics.

Parametric spatial covariance models in the ensemble Kalman filter

Jacob Skauvold, Jo Eidsvik, 2019 .

Learning excursion sets of vector-valued Gaussian random fields for autonomous ocean sampling pdf

David Ginsbourger, Jo Eidsvik, Kanna Rajan, 2020, ArXiv.

Value of information in spatial decision situations

Tapan Mukerji, Debarun Bhattacharjya, Jo Eidsvik, 2015 .

Efficient designs for Bayesian networks with sub-tree bounds

Jo Eidsvik, Marie Lilleborge, J. Eidsvik, 2015, Statistics and Computing.

LIDAR Extended Object Tracking of a Maritime Vessel Using an Ellipsoidal Contour Model

Edmund Førland Brekke, Jo Eidsvik, Kristian Amundsen Ruud, 2018, 2018 Sensor Data Fusion: Trends, Solutions, Applications (SDF).

Information‐driven robotic sampling in the coastal ocean

Martin Ludvigsen, Jo Eidsvik, Geir Johnsen, 2018, J. Field Robotics.

Value of Information Analysis of Geophysical Data for Spatial Decision Situations

Tapan Mukerji, Debarun Bhattacharjya, Jo Eidsvik, 2015 .

Assessing the value of seismic monitoring of CO2 storage using simulations and statistical analysis

Jo Eidsvik, Per Bergmo, Anouar Romdhane, 2021 .

Efficient spatial designs using Hausdorff distances and Bayesian optimization

Juha Karvanen, Jo Eidsvik, Jacopo Paglia, 2021, Scandinavian Journal of Statistics.

Seismic reservoir prediction using Bayesian integration of rock physics and Markov random fields: A North Sea example

Tapan Mukerji, Henning Omre, Jo Eidsvik, 2002 .

Stochastic reservoir characterization using prestack seismic data

Tapan Mukerji, Henning Omre, Jo Eidsvik, 2004 .

Value of information analysis and Bayesian inversion for closed skew-normal distributions: Applications to seismic amplitude variation with offset data

Tapan Mukerji, Javad Rezaie, Jo Eidsvik, 2014 .

Value of information of seismic amplitude and CSEM resistivity

Tapan Mukerji, Debarun Bhattacharjya, Jo Eidsvik, 2008 .

Data assimilation for a geological process model using the ensemble Kalman filter

Jacob Skauvold, Jo Eidsvik, J. Eidsvik, 2017, 1711.07763.

A Fused Lasso Approach to Nonstationary Spatial Covariance Estimation

Jo Eidsvik, Brian J. Reich, Ryan J. Parker, 2016 .

Shrinked (1 − α) ensemble Kalman filter and α Gaussian mixture filter

Javad Rezaie, Jo Eidsvik, J. Eidsvik, 2012 .

Analysis of prior models for a blocky inversion of seismic AVA data

Jo Eidsvik, Ulrich Theune, J. Eidsvik, 2010 .

Positioning and Position Error of Petroleum Wells

Jo Eidsvik, Bjorn Tornstein Bruun, Erik Nyrnes, 2011 .

A class of covariate-dependent spatiotemporal covariance functions.

Jo Eidsvik, Michele Guindani, Brian J Reich, 2011, The annals of applied statistics.