63 citations · 227 across the 34 of their papers we have counts for
42 papers
Coherent Information Deletion: Bayesian, Generalized Bayesian and Possibilistic Unlearning
Hans Montcho, Håvard Rue, Maurizio Filippone
Bayes' theorem admits an information processing interpretation due to Zellner (1988): under the Shannon information criterion, the posterior is the unique rule that processes prior…
Integrated Nested Laplace Approximations for Large-Scale Spatial-Temporal Bayesian Modeling
Lisa Gaedke-Merzhäuser, Elias Krainski, Radim Janalik +2
Bayesian inference tasks continue to pose a computational challenge. This especially holds for spatial-temporal modeling where high-dimensional latent parameter spaces are ubiquito…
A new avenue for Bayesian inference with INLA
Janet van Niekerk, Elias Krainski, Denis Rustand +1
Integrated Nested Laplace Approximations (INLA) has been a successful approximate Bayesian inference framework since its proposal by Rue et al. (2009). The increased computational…
Parallelized integrated nested Laplace approximations for fast Bayesian inference
Lisa Gaedke-Merzhäuser, Janet van Niekerk, Olaf Schenk +1
There is a growing demand for performing larger-scale Bayesian inference tasks, arising from greater data availability and higher-dimensional model parameter spaces. In this work w…
Fast and flexible inference for joint models of multivariate longitudinal and survival data using Integrated Nested Laplace Approximations
Denis Rustand, Janet van Niekerk, Elias Teixeira Krainski +2
Modeling longitudinal and survival data jointly offers many advantages such as addressing measurement error and missing data in the longitudinal processes, understanding and quanti…
Joint Posterior Inference for Latent Gaussian Models with R-INLA
Cristian Chiuchiolo, Janet van Niekerk, Haavard Rue
Efficient Bayesian inference remains a computational challenge in hierarchical models. Simulation-based approaches such as Markov Chain Monte Carlo methods are still popular but ha…