Posterior inference for sparse hierarchical non-stationary models
From MaRDI portal
Publication:2189583
DOI10.1016/j.csda.2020.106954OpenAlexW3010999265MaRDI QIDQ2189583
Sara Wade, Lassi Roininen, Karla Monterrubio-Gómez, Theodoros Damoulas, Mark A. Girolami
Publication date: 16 June 2020
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1804.01431
Related Items (7)
Nonstationary Gaussian Process Discriminant Analysis With Variable Selection for High-Dimensional Functional Data ⋮ Deep Compositional Spatial Models ⋮ Stochastic variational inference for scalable non-stationary Gaussian process regression ⋮ Multi-scale process modelling and distributed computation for spatial data ⋮ Non-stationary multi-layered Gaussian priors for Bayesian inversion ⋮ Deep state-space Gaussian processes ⋮ The SPDE approach to Matérn fields: graph representations
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach
- A comparative evaluation of stochastic-based inference methods for Gaussian process models
- Nonstationary modeling for multivariate spatial processes
- Linear smoothers and additive models
- Hyperpriors for Matérn fields with applications in Bayesian inversion
- Bayesian adaptive smoothing splines using stochastic differential equations
- A case study competition among methods for analyzing large spatial data
- Estimating deformations of isotropic Gaussian random fields on the plane
- Bayesian Treed Gaussian Process Models With an Application to Computer Modeling
- Adapting to Unknown Smoothness via Wavelet Shrinkage
- Exploring a New Class of Non-stationary Spatial Gaussian Random Fields with Varying Local Anisotropy
- The intrinsic random functions and their applications
- Nonstationary inverse problems and state estimation
- How Deep Are Deep Gaussian Processes?
- Computer Emulation with Nonstationary Gaussian Processes
- Gaussian Markov Random Fields
- Covariance Structure of Wavelet Coefficients: Theory and Models in a Bayesian Perspective
- Diagnostics-Driven Nonstationary Emulators Using Kernel Mixtures
- Auxiliary Gradient-Based Sampling Algorithms
- Probabilistic Weather Forecasting for Winter Road Maintenance
- Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics
- Analyzing Nonstationary Spatial Data Using Piecewise Gaussian Processes
This page was built for publication: Posterior inference for sparse hierarchical non-stationary models