Cover Image

The BdryMatérn GP: Reliable incorporation of boundary information on irregular domains for Gaussian process modeling

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ding, Liang, Mak, Simon, Wu, C. F. Jeff
Format:	Preprint
Published:	2025
Subjects:	Methodology Statistics Theory Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Rolled Gaussian process models for curves on manifolds
by: Preston, Simon, et al.
Published: (2025)

Adaptive finite element type decomposition of Gaussian processes
by: Kim, Jaehoan, et al.
Published: (2025)

Fast kernel methods: Sobolev, physics-informed, and additive models
by: Doumèche, Nathan, et al.
Published: (2025)

Random irregular histograms
by: Simensen, Oskar Høgberg, et al.
Published: (2025)

Minimax optimal adaptive structured transfer learning through semi-parametric domain-varying coefficient model
by: Chen, Hanxiao, et al.
Published: (2026)

Microergodicity implies orthogonality of Matérn fields on bounded domains in $\mathbb{R}^4$
by: Pillai, Natesh S.
Published: (2026)

Partial correlation networks of Gaussian processes
by: Peruzzi, Michele
Published: (2026)

Discrete Gaussian Vector Fields On Meshes
by: Gillan, Michael, et al.
Published: (2025)

Deep learning estimation of the spectral density of functional time series on large domains
by: Mohammadi, Neda, et al.
Published: (2026)

Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices
by: de Surrel, Thibault, et al.
Published: (2025)

Estimation and model errors in Gaussian-process-based Sensitivity Analysis of functional outputs
by: Sáo, Yuri Taglieri, et al.
Published: (2025)

Adaptive Confidence Intervals in Efron's Gaussian Two-Groups Model
by: Wang, Qiaosen, et al.
Published: (2026)

Scalable Bayesian inference for heat kernel Gaussian processes on manifolds
by: He, Junhui, et al.
Published: (2024)

Profile monitoring of random functions with Gaussian process basis expansions
by: Iguchi, Takayuki, et al.
Published: (2025)

Model-agnostic information transfer and fusion for classification with label noise
by: Guojun, Zhu, et al.
Published: (2026)

A renormalization-group inspired lattice-based framework for piecewise generalized linear models
by: Chang, Joshua C.
Published: (2026)

Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
by: Tian, Ye, et al.
Published: (2022)

Anytime-valid t-tests and confidence sequences for Gaussian means with unknown variance
by: Wang, Hongjian, et al.
Published: (2023)

Large-Sample Properties of Non-Stationary Source Separation for Gaussian Signals
by: Bachoc, François, et al.
Published: (2022)

Powerful rank verification for multivariate Gaussian data with any covariance structure
by: Sood, Anav
Published: (2025)

Matern Correlation: A Panoramic Primer
by: Chen, Xiaoqing
Published: (2024)

Fast and Provably Accurate Sequential Designs using Hilbert Space Gaussian Processes
by: Zhu, Huanyan, et al.
Published: (2026)

Increasing domain asymptotics for covariate-based nonparametric Bayesian intensity estimation with Gaussian and Besov-Laplace priors
by: Dolmeta, Patric, et al.
Published: (2026)

Using prior information to boost power in correlation structure support recovery
by: Ding, Ziyang, et al.
Published: (2021)

Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case
by: Azangulov, Iskander, et al.
Published: (2022)

Multivariate Matérn Models -- A Spectral Approach
by: Yarger, Drew, et al.
Published: (2023)

Model Selection for Gaussian-gated Gaussian Mixture of Experts Using Dendrograms of Mixing Measures
by: Thai, Tuan, et al.
Published: (2025)

On goodness-of-fit testing for self-exciting point processes
by: Kling, José C. F., et al.
Published: (2024)

Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces
by: Azangulov, Iskander, et al.
Published: (2023)

Sparsity meets correlation in Gaussian sequence model
by: Kotekal, Subhodh, et al.
Published: (2023)

Algebraic and Statistical Properties of the Ordinary Least Squares Interpolator
by: Shen, Dennis, et al.
Published: (2023)

Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions
by: Bing, Simon, et al.
Published: (2023)

Conditional independence testing with a single realization of a multivariate nonstationary nonlinear time series
by: Wieck-Sosa, Michael, et al.
Published: (2025)

Maximum-likelihood estimation of the Matérn covariance structure of isotropic spatial random fields on finite, sampled grids
by: Simons, Frederik J., et al.
Published: (2025)

Classification by sparse generalized additive models
by: Abramovich, Felix
Published: (2022)

Reversible Gromov-Monge Sampler for Simulation-Based Inference
by: Hur, YoonHaeng, et al.
Published: (2021)

Finite sample-optimal adjustment sets in linear Gaussian causal models
by: Rutsch, Nadja, et al.
Published: (2025)

A general framework for inference on algorithm-agnostic variable importance
by: Williamson, Brian D., et al.
Published: (2020)

Locally minimax optimal confidence sets for the best model
by: Kim, Ilmun, et al.
Published: (2025)

A structural equation formulation for general quasi-periodic Gaussian processes
by: Nigam, Unnati, et al.
Published: (2025)