Pages that link to "Item:Q68580"

The following pages link to An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach (Q68580):

Displaying 50 items.

• Approximate inference for spatial functional data on massively parallel processors (Q1623412) (← links)
• Weak convergence of Galerkin approximations for fractional elliptic stochastic PDEs with spatial white noise (Q1631188) (← links)
• Modeling skewed spatial data using a convolution of Gaussian and log-Gaussian processes (Q1631562) (← links)
• Big data sampling and spatial analysis: ``which of the two ladles, of fig-wood or gold, is appropriate to the soup and the pot?'' (Q1642391) (← links)
• Principles for statistical inference on big spatio-temporal data from climate models (Q1642392) (← links)
• A multi-resolution model for non-Gaussian random fields on a sphere with application to ionospheric electrostatic potentials (Q1647630) (← links)
• Reducing storage of global wind ensembles with stochastic generators (Q1647632) (← links)
• High resolution simulation of nonstationary Gaussian random fields (Q1659084) (← links)
• Modeling spatial anisotropy via regression with partial differential regularization (Q1661326) (← links)
• Spatial data compression via adaptive dispersion clustering (Q1662049) (← links)
• Bayesian calibration of blue crab (\textit{callinectes sapidus}) abundance indices based on probability surveys (Q1695259) (← links)
• Statistical analysis of differential equations: introducing probability measures on numerical solutions (Q1703820) (← links)
• Modified Cholesky Riemann manifold Hamiltonian Monte Carlo: exploiting sparsity for fast sampling of high-dimensional targets (Q1704017) (← links)
• Spherical process models for global spatial statistics (Q1704699) (← links)
• sppmix: Poisson point process modeling using normal mixture models (Q1729311) (← links)
• Two-scale spatial models for binary data (Q1742839) (← links)
• Fast generation of isotropic Gaussian random fields on the sphere (Q1746424) (← links)
• Statistical analysis of complex and spatially dependent data: a review of object oriented spatial statistics (Q1751652) (← links)
• Bayesian spectral modeling for multivariate spatial distributions of elemental concentrations in soil (Q1752000) (← links)
• Mitigating the influence of the boundary on PDE-based covariance operators (Q1785028) (← links)
• On Russian roulette estimates for Bayesian inference with doubly-intractable likelihoods (Q1790298) (← links)
• Penalising model component complexity: a principled, practical approach to constructing priors (Q1790379) (← links)
• INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles (Q1792632) (← links)
• Latent Gaussian random field mixture models (Q1799875) (← links)
• A dynamic nonstationary spatio-temporal model for short term prediction of precipitation (Q1939996) (← links)
• A toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA) (Q1939998) (← links)
• Spatial models for point and areal data using Markov random fields on a fine grid (Q1951143) (← links)
• A Bayesian level set method for an inverse medium scattering problem in acoustics (Q1983455) (← links)
• Bayesian inference of random fields represented with the Karhunen-Loève expansion (Q1989096) (← links)
• Hybrid simulation scheme for volatility modulated moving average fields (Q1997699) (← links)
• Bayesian spatio-temporal prediction of cancer dynamics (Q2006230) (← links)
• A hierarchical spatiotemporal statistical model motivated by glaciology (Q2009141) (← links)
• Fractional calculus: quo vadimus? (where are we going?) (Q2017477) (← links)
• The statistical finite element method (statFEM) for coherent synthesis of observation data and model predictions (Q2022037) (← links)
• Bayesian space-time gap filling for inference on extreme hot-spots: an application to Red Sea surface temperatures (Q2028571) (← links)
• Spatio-temporal prediction of missing temperature with stochastic Poisson equations. The LC2019 team winning entry for the EVA 2019 data competition (Q2028576) (← links)
• Spatiotemporal probabilistic wind vector forecasting over Saudi Arabia (Q2044259) (← links)
• Intuitive joint priors for variance parameters (Q2057345) (← links)
• Where is the clean air? A Bayesian decision framework for personalised cyclist route selection using R-INLA (Q2057372) (← links)
• Deep state-space Gaussian processes (Q2058900) (← links)
• Derivative-informed projected neural networks for high-dimensional parametric maps governed by PDEs (Q2060092) (← links)
• Bayesian prediction of spatial data with non-ignorable missingness (Q2062380) (← links)
• Urban planning image feature enhancement and simulation based on partial differential equation method (Q2064673) (← links)
• Stochastic local interaction model: an alternative to kriging for massive datasets (Q2066859) (← links)
• Score matching filters for Gaussian Markov random fields with a linear model of the precision matrix (Q2072672) (← links)
• A general framework for SPDE-based stationary random fields (Q2073200) (← links)
• Estimating animal utilization distributions from multiple data types: a joint spatiotemporal point process framework (Q2078306) (← links)
• Integrating geostatistical maps and infectious disease transmission models using adaptive multiple importance sampling (Q2078318) (← links)
• A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes (Q2080349) (← links)
• Kryging: geostatistical analysis of large-scale datasets using Krylov subspace methods (Q2080350) (← links)