Cover Image

Further Understanding of a Local Gaussian Process Approximation: Characterising Convergence in the Finite Regime

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Stephenson, Anthony, Allison, Robert, Pyzer-Knapp, Edward
Format:	Preprint
Published:	2024
Subjects:	Statistics Theory Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures
by: Li, Gen, et al.
Published: (2025)

Finite-Dimensional Gaussian Approximation for Deep Neural Networks: Universality in Random Weights
by: Balasubramanian, Krishnakumar, et al.
Published: (2025)

PAC-Chernoff Bounds: Understanding Generalization in the Interpolation Regime
by: Masegosa, Andrés R., et al.
Published: (2023)

Approximation of Maximally Monotone Operators : A Graph Convergence Perspective
by: Furuya, Takashi, et al.
Published: (2026)

Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean-Field Games
by: Ocello, Antonio, et al.
Published: (2025)

Finite-Sample Wasserstein Error Bounds and Concentration Inequalities for Nonlinear Stochastic Approximation
by: Kong, Seo Taek, et al.
Published: (2026)

Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent
by: Banerjee, Sayan, et al.
Published: (2024)

Local Minima Structures in Gaussian Mixture Models
by: Chen, Yudong, et al.
Published: (2020)

Data-driven Learning of Interaction Laws in Multispecies Particle Systems with Gaussian Processes: Convergence Theory and Applications
by: Feng, Jinchao, et al.
Published: (2025)

Estimating the Number of Components in Finite Mixture Models via Variational Approximation
by: Wang, Chenyang, et al.
Published: (2024)

The Theory and Practice of Highly Scalable Gaussian Process Regression with Nearest Neighbours
by: Allison, Robert, et al.
Published: (2026)

Bounds in Wasserstein Distance for Locally Stationary Processes
by: Tinio, Jan Nino G., et al.
Published: (2024)

Finite-Particle Convergence Rates for Conservative and Non-Conservative Drifting Models
by: Balasubramanian, Krishnakumar
Published: (2026)

Multivariate Gaussian Approximation for Random Forest via Region-based Stabilization
by: Shi, Zhaoyang, et al.
Published: (2024)

A Fine-Grained Understanding of Uniform Convergence for Halfspaces
by: Kontorovich, Aryeh, et al.
Published: (2026)

Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data
by: Fu, Hengyu, et al.
Published: (2024)

Geometric Gaussian Approximations of Probability Distributions
by: Da Costa, Nathaël, et al.
Published: (2025)

Hypothesis Testing over Observable Regimes in Singular Models
by: Plummer, Sean
Published: (2026)

Sample Path Regularity of Gaussian Processes from the Covariance Kernel
by: Da Costa, Nathaël, et al.
Published: (2023)

Asymptotics of Random Feature Regression Beyond the Linear Scaling Regime
by: Hu, Hong, et al.
Published: (2024)

Posterior Covariance Structures in Gaussian Processes
by: Cai, Difeng, et al.
Published: (2024)

Gaussian Process Upper Confidence Bounds in Distributed Point Target Tracking over Wireless Sensor Networks
by: Liu, Xingchi, et al.
Published: (2024)

Post-Hoc Uncertainty Quantification in Pre-Trained Neural Networks via Activation-Level Gaussian Processes
by: Bergna, Richard, et al.
Published: (2025)

Gaussian and Bootstrap Approximation for Matching-based Average Treatment Effect Estimators
by: Shi, Zhaoyang, et al.
Published: (2024)

Targeted Separation and Convergence with Kernel Discrepancies
by: Barp, Alessandro, et al.
Published: (2022)

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

Gaussian and Non-Gaussian Universality of Data Augmentation
by: Huang, Kevin Han, et al.
Published: (2022)

Wasserstein Convergence of Critically Damped Langevin Diffusions
by: Strasman, Stanislas, et al.
Published: (2025)

Optimal Convergence Analysis of DDPM for General Distributions
by: Jiao, Yuchen, et al.
Published: (2025)

Deep Horseshoe Gaussian Processes
by: Castillo, Ismaël, et al.
Published: (2024)

On Multiple Robustness of Proximal Dynamic Treatment Regimes
by: Gao, Yuanshan, et al.
Published: (2025)

Gaussian Process Regression under Computational and Epistemic Misspecification
by: Sanz-Alonso, Daniel, et al.
Published: (2023)

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

Linear Convergence of Diffusion Models Under the Manifold Hypothesis
by: Potaptchik, Peter, et al.
Published: (2024)

Convergence of Statistical Estimators via Mutual Information Bounds
by: Khribch, El Mahdi, et al.
Published: (2024)

Simplicity Bias via Global Convergence of Sharpness Minimization
by: Gatmiry, Khashayar, et al.
Published: (2024)

Statistical Convergence of Spherical First Hitting Diffusion Models
by: Bienewald, Simon, et al.
Published: (2026)

Approximation of RKHS Functionals by Neural Networks
by: Zhou, Tian-Yi, et al.
Published: (2024)

Approximate full conformal prediction in an RKHS
by: Razafindrakoto, Davidson Lova, et al.
Published: (2026)

Diffusion Approximations for Thompson Sampling in the Small Gap Regime
by: Fan, Lin, et al.
Published: (2021)