:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Giordano, Matteo, Kirichenko, Alisa, Rousseau, Judith
Format:	Preprint
Published:	2023
Subjects:	Statistics Theory
Online Access:	https://arxiv.org/abs/2312.14073
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

A nonparametric Bayesian analysis of independent and identically distributed observations of covariate-driven Poisson processes
by: Dolmeta, Patric, et al.
Published: (2025)

Bayesian Nonparametric Inference in Elliptic PDEs: Convergence Rates and Implementation
by: Giordano, Matteo
Published: (2023)

Bayesian inference with Besov-Laplace priors for spatially inhomogeneous binary classification surfaces
by: Giordano, Matteo
Published: (2025)

Asymptotic guarantees for Bayesian phylogenetic tree reconstruction
by: Kirichenko, Alisa, et al.
Published: (2025)

Nonparametric Bayesian inference for reversible multi-dimensional diffusions
by: Giordano, Matteo, et al.
Published: (2020)

Hierarchical Besov-Laplace priors for spatially inhomogeneous binary classification
by: Dolmeta, Patric, et al.
Published: (2025)

Estimation in linear high dimensional Hawkes processes: a Bayesian approach
by: Rousseau, Judith, et al.
Published: (2025)

Bayesian Inference for Initial Heat States with Gaussian Series Priors
by: Giordano, Matteo
Published: (2025)

Empirical Bayes in Bayesian learning: understanding a common practice
by: Rizzelli, Stefano, et al.
Published: (2024)

Nonparametric regression on random geometric graphs sampled from submanifolds
by: Rosa, Paul, et al.
Published: (2024)

Nonparametric estimation of linear multiplier for processes driven by a Hermite process
by: Rao, B. L. S. Prakasa
Published: (2026)

A Bayesian approach with Gaussian priors to the inverse problem of source identification in elliptic PDEs
by: Giordano, Matteo
Published: (2024)

On sparsity, power-law and clustering properties of graphex processes
by: Caron, François, et al.
Published: (2017)

Nonparametric estimation of linear multiplier for processes driven by a bifractional Brownian motion
by: Rao, B. L. S. Prakasa
Published: (2024)

Nonparametric density estimation for the small jumps of Lévy processes
by: Duval, Céline, et al.
Published: (2024)

An unbounded intensity model for point processes
by: Christensen, Kim, et al.
Published: (2024)

Tuning-free one-bit covariance estimation using data-driven dithering
by: Dirksen, Sjoerd, et al.
Published: (2023)

Asymptotic analysis for covariance parameter estimation of Gaussian processes with functional inputs
by: Reding, Lucas, et al.
Published: (2024)

Asymptotic Analysis of Statistical Estimators related to MultiGraphex Processes under Misspecification
by: Naulet, Zacharie, et al.
Published: (2021)

The Bernstein-von Mises theorem and efficiency for semiparametric inference in multivariate Hawkes processes
by: Duverger, Mael, et al.
Published: (2026)

Bayesian Nonparametric Inference for "Species-sampling" Problems
by: Balocchi, Cecilia, et al.
Published: (2022)

Estimating a density near an unknown manifold: a Bayesian nonparametric approach
by: Berenfeld, Clément, et al.
Published: (2022)

Semiparametric Bernstein-von Mises theorems for reversible diffusions
by: Giordano, Matteo, et al.
Published: (2025)

Gaussian Process Methods for Covariate-Based Intensity Estimation
by: Dolmeta, Patric, et al.
Published: (2025)

Nonparametric estimation of FBSDEs with random terminal time
by: Ji, Shaolin, et al.
Published: (2024)

Nonparametric local polynomial regression for functional covariates
by: Jirak, Moritz, et al.
Published: (2025)

Variational Bayesian Bow tie Neural Networks with Shrinkage
by: Sheinkman, Alisa, et al.
Published: (2024)

Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions
by: Azangulov, Iskander, et al.
Published: (2024)

Spatio-temporal point process intensity estimation using zero-deflated subsampling applied to a lightning strikes dataset in France
by: Coeurjolly, Jean-François, et al.
Published: (2024)

Separate Exchangeability as Modeling Principle in Bayesian Nonparametrics
by: Rebaudo, Giovanni, et al.
Published: (2021)

The Bayesian Infinitesimal Jackknife for Variance
by: Giordano, Ryan, et al.
Published: (2023)

Nonparametric estimation of trend for stochastic differential equations driven by multiplicative stochastic volatility
by: Rao, B. L. S. Prakasa
Published: (2024)

Nonparametric optimal density estimation for censored circular data
by: Conanec, Nicolas, et al.
Published: (2025)

Asymptotic properties of maximum likelihood estimators for determinantal point processes
by: Hu, Yaozhong, et al.
Published: (2023)

Marked point processes intensity estimation using sparse group Lasso method applied to locations of lucrative and cooperative banks in mainland France
by: Artis, Amélie, et al.
Published: (2025)

Nonparametric, tuning-free estimation of S-shaped functions
by: Feng, Oliver Y., et al.
Published: (2021)

On the orthogonally equivariant estimators of a covariance matrix
by: Tsai, Ming-Tien, et al.
Published: (2024)

Nonparametric quantile regression for spatio-temporal processes
by: Deb, Soudeep, et al.
Published: (2024)

Nonparametric estimation of linear multiplier for stochastic differential equations driven by multiplicative stochastic volatility
by: Rao, B. L. S Prakasa
Published: (2024)