Convergence rates of non-stationary and deep Gaussian process regression
Fuente:
arXiv
Saved in:
| Main Authors: | Osborne, Conor, Teckentrup, Aretha L. |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adaptive thresholding for wavelet-based nonparametric heteroskedastic variance estimation on the sphere
by: Durastanti, Claudio, et al.
Published: (2026)
by: Durastanti, Claudio, et al.
Published: (2026)
Model-free filtering in high dimensions via projection and score-based diffusions
by: Christensen, Sören, et al.
Published: (2025)
by: Christensen, Sören, et al.
Published: (2025)
Nonparametric density estimation for stationary processes under multiplicative measurement errors
by: Dang, Duc Trong, et al.
Published: (2024)
by: Dang, Duc Trong, et al.
Published: (2024)
On the Convergence of the ELBO to Entropy Sums
by: Lücke, Jörg, et al.
Published: (2022)
by: Lücke, Jörg, et al.
Published: (2022)
Sparse semiparametric regression when predictors are mixture of functional and high-dimensional variables
by: Novo, Silvia, et al.
Published: (2024)
by: Novo, Silvia, et al.
Published: (2024)
Generative Models with ELBOs Converging to Entropy Sums
by: Warnken, Jan, et al.
Published: (2024)
by: Warnken, Jan, et al.
Published: (2024)
Dirichlet kernel density estimation on the simplex with missing data
by: Daayeb, Hanen, et al.
Published: (2026)
by: Daayeb, Hanen, et al.
Published: (2026)
Kernel Density Estimation and Convolution Revisited
by: Tenkorang, Nicholas, et al.
Published: (2025)
by: Tenkorang, Nicholas, et al.
Published: (2025)
Adaptation using spatially distributed Gaussian Processes
by: Szabo, Botond, et al.
Published: (2023)
by: Szabo, Botond, et al.
Published: (2023)
A hybrid-Hill estimator enabled by heavy-tailed block maxima
by: Neves, Claudia, et al.
Published: (2025)
by: Neves, Claudia, et al.
Published: (2025)
Estimation of the invariant measure of a multidimensional diffusion from noisy observations
by: Maillet, Raphaël, et al.
Published: (2024)
by: Maillet, Raphaël, et al.
Published: (2024)
Asymptotic confidence bands for the histogram regression estimator
by: Neumeyer, Natalie, et al.
Published: (2025)
by: Neumeyer, Natalie, et al.
Published: (2025)
An energy-based deep splitting method for the nonlinear filtering problem
by: Bågmark, Kasper, et al.
Published: (2022)
by: Bågmark, Kasper, et al.
Published: (2022)
The Cost of Adaptation under Differential Privacy: Optimal Adaptive Federated Density Estimation
by: Cai, T. Tony, et al.
Published: (2025)
by: Cai, T. Tony, et al.
Published: (2025)
Dirichlet kernel density estimation for strongly mixing sequences on the simplex
by: Daayeb, Hanen, et al.
Published: (2025)
by: Daayeb, Hanen, et al.
Published: (2025)
A Bernstein polynomial approach for the estimation of cumulative distribution functions in the presence of missing data
by: Gharbi, Rihab, et al.
Published: (2025)
by: Gharbi, Rihab, et al.
Published: (2025)
TILT: Target-induced loss tilting under covariate shift
by: Yamamoto, Kakei, et al.
Published: (2026)
by: Yamamoto, Kakei, et al.
Published: (2026)
Minimax rates for learning kernels in operators
by: Zhang, Sichong, et al.
Published: (2025)
by: Zhang, Sichong, et al.
Published: (2025)
Semi-functional partial linear regression with measurement error: An approach based on $k$NN estimation
by: Novo, Silvia, et al.
Published: (2024)
by: Novo, Silvia, et al.
Published: (2024)
Mean and Covariance Estimation for Discretely Observed High-Dimensional Functional Data: Rates of Convergence and Division of Observational Regimes
by: Petersen, Alexander
Published: (2024)
by: Petersen, Alexander
Published: (2024)
High-dimensional Bayesian filtering through deep density approximation
by: Bågmark, Kasper, et al.
Published: (2025)
by: Bågmark, Kasper, et al.
Published: (2025)
Nonlinear filtering based on density approximation and deep BSDE prediction
by: Bågmark, Kasper, et al.
Published: (2025)
by: Bågmark, Kasper, et al.
Published: (2025)
Asymptotic equivalence of non-parametric regression with spherical regressors and Gaussian white noise
by: Kroll, Martin
Published: (2025)
by: Kroll, Martin
Published: (2025)
Kernel Density Machines
by: Della Vecchia, Andrea, et al.
Published: (2025)
by: Della Vecchia, Andrea, et al.
Published: (2025)
Nonparametric estimation of trawl processes: Theory and applications
by: Sauri, Orimar, et al.
Published: (2022)
by: Sauri, Orimar, et al.
Published: (2022)
Least squares approximations in linear statistical inverse learning problems
by: Helin, Tapio
Published: (2022)
by: Helin, Tapio
Published: (2022)
Is model selection possible for the $\ell_p$-loss? PCO estimation for regression models
by: Lacour, Claire, et al.
Published: (2025)
by: Lacour, Claire, et al.
Published: (2025)
Single-index models for extreme value index regression
by: Yoshida, Takuma
Published: (2022)
by: Yoshida, Takuma
Published: (2022)
A convergent scheme for the Bayesian filtering problem based on the Fokker--Planck equation and deep splitting
by: Bågmark, Kasper, et al.
Published: (2024)
by: Bågmark, Kasper, et al.
Published: (2024)
A $k$NN procedure in semiparametric functional data analysis
by: Novo, Silvia, et al.
Published: (2024)
by: Novo, Silvia, et al.
Published: (2024)
Distributional Conformal Prediction for Markov Processes
by: Dai, Dehao, et al.
Published: (2026)
by: Dai, Dehao, et al.
Published: (2026)
Invariant quantile regression for heterogeneous environments
by: Fu, Bo, et al.
Published: (2026)
by: Fu, Bo, et al.
Published: (2026)
Identifying arbitrary transformation between the slopes in scalar-on-function regression
by: Niyogi, Pratim Guha, et al.
Published: (2024)
by: Niyogi, Pratim Guha, et al.
Published: (2024)
Spatio-temporal probabilistic forecast using MMAF-guided learning
by: Bardi, Leonardo, et al.
Published: (2026)
by: Bardi, Leonardo, et al.
Published: (2026)
Variance-Reduced Manifold Sampling via Polynomial-Maximization Density Estimation
by: Zabolotnii, Serhii
Published: (2026)
by: Zabolotnii, Serhii
Published: (2026)
Blessing of dimensionality in cross-validated bandwidth selection on the sphere
by: Chacón, José E., et al.
Published: (2026)
by: Chacón, José E., et al.
Published: (2026)
A kernel-based framework for covariate significance tests in nonparametric regression
by: Diz-Castro, Daniel, et al.
Published: (2025)
by: Diz-Castro, Daniel, et al.
Published: (2025)
Optimal minimax rate of learning nonlocal interaction kernels
by: Wang, Xiong, et al.
Published: (2023)
by: Wang, Xiong, et al.
Published: (2023)
Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints
by: Auddy, Arnab, et al.
Published: (2024)
by: Auddy, Arnab, et al.
Published: (2024)
Factor Informed Double Deep Learning For Average Treatment Effect Estimation
by: Fan, Jianqing, et al.
Published: (2025)
by: Fan, Jianqing, et al.
Published: (2025)
Similar Items
-
Adaptive thresholding for wavelet-based nonparametric heteroskedastic variance estimation on the sphere
by: Durastanti, Claudio, et al.
Published: (2026) -
Model-free filtering in high dimensions via projection and score-based diffusions
by: Christensen, Sören, et al.
Published: (2025) -
Nonparametric density estimation for stationary processes under multiplicative measurement errors
by: Dang, Duc Trong, et al.
Published: (2024) -
On the Convergence of the ELBO to Entropy Sums
by: Lücke, Jörg, et al.
Published: (2022) -
Sparse semiparametric regression when predictors are mixture of functional and high-dimensional variables
by: Novo, Silvia, et al.
Published: (2024)