Sparse Approximate Inference for Spatio-Temporal Point Process Models

A Case Study for Modelling Cancer Incidence Using Bayesian Spatio-Temporal Models

(2015) Su Yun Kang et al.   AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS

Variational Estimation in Spatiotemporal Systems From Continuous and Point-Process Observations

(2012) A. Zammit-Mangion et al.   IEEE TRANSACTIONS ON SIGNAL PROCESSING

Markov Chain Monte Carlo Methods for State-Space Models with Point Process Observations

(2012) Ke Yuan et al.   NEURAL COMPUTATION

Point process modelling of the Afghan War Diary

(2012) A. Zammit-Mangion et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach

(2011) Finn Lindgren et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Riemann manifold Langevin and Hamiltonian Monte Carlo methods

(2011) Mark Girolami et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations

(2009) Håvard Rue et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

The Variational Gaussian Approximation Revisited

(2008) Manfred Opper et al.   NEURAL COMPUTATION

Covariance selection for nonchordal graphs via chordal embedding

(2008) Joachim Dahl et al.   OPTIMIZATION METHODS & SOFTWARE