Jo Eidsvik

Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations

Location and scale mixtures of Gaussians with flexible tail behaviour: Properties, inference and application to multivariate clustering

Flexible paleoclimate age-depth models using an autoregressive gamma process

Fast Stable Restricted Maximum Likelihood and Marginal Likelihood Estimation of Semiparametric Generalized Linear Models

Benchmarking railway vibrations – Track, vehicle, ground and building effects

Bayesian computing with INLA: New features

Flexible paleoclimate age-depth models using an autoregressive gamma process

A general purpose sampling algorithm for continuous distributions (the t-walk)

A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems

Geostatistical Inference Under Preferential Sampling

Physics-informed machine learning

Parameter and State Model Reduction for Large-Scale Statistical Inverse Problems

glmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling

Finite Mixture Models

A robotic Intelligent Towing Tank for learning complex fluid-structure dynamics

A probabilistic assessment of resolution in the SASW test and its impact on the prediction of ground vibrations

An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach

A general purpose sampling algorithm for continuous distributions (the t-walk)

Approximate Bayesian Inference in Spatial Generalized Linear Mixed Models

Approximate Bayesian inference in spatial GLMM with skew normal latent variables

On directional Metropolis–Hastings algorithms

Positioning and Position Error of Petroleum Wells

Toward adaptive robotic sampling of phytoplankton in the coastal ocean

Approximate Bayesian inference for large spatial datasets using predictive process models