Cover Image

Model-free filtering in high dimensions via projection and score-based diffusions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Christensen, Sören, Kallsen, Jan, Strauch, Claudia, Trottner, Lukas
Format:	Preprint
Published:	2025
Subjects:	Statistics Theory Machine Learning 62C10, 62G20, 62G05, 60J65, 68T07
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning to reflect: A unifying approach for data-driven stochastic control strategies
by: Christensen, Sören, et al.
Published: (2021)

Estimation of the invariant measure of a multidimensional diffusion from noisy observations
by: Maillet, Raphaël, et al.
Published: (2024)

Nonparametric density estimation for stationary processes under multiplicative measurement errors
by: Dang, Duc Trong, et al.
Published: (2024)

Convergence rates of non-stationary and deep Gaussian process regression
by: Osborne, Conor, et al.
Published: (2023)

Dirichlet kernel density estimation for strongly mixing sequences on the simplex
by: Daayeb, Hanen, et al.
Published: (2025)

Concentration analysis of multivariate elliptic diffusion processes
by: Aeckerle-Willems, Cathrine, et al.
Published: (2022)

Kernel Density Machines
by: Della Vecchia, Andrea, et al.
Published: (2025)

Adaptive Density Estimation Using Projection Kernels and Penalized Comparison to Overfitting
by: Hoang, Van Ha, et al.
Published: (2025)

An effective estimation of multivariate density functions using extended-beta kernels with Bayesian adaptive bandwidths
by: Somé, Sobom M., et al.
Published: (2025)

A hybrid-Hill estimator enabled by heavy-tailed block maxima
by: Neves, Claudia, et al.
Published: (2025)

Wishart kernel density estimation for strongly mixing time series on the cone of positive definite matrices
by: Belzile, Léo R., et al.
Published: (2025)

High-dimensional Bayesian filtering through deep density approximation
by: Bågmark, Kasper, et al.
Published: (2025)

Nonlinear filtering based on density approximation and deep BSDE prediction
by: Bågmark, Kasper, et al.
Published: (2025)

Minimax properties of gamma kernel density estimators under $L^p$ loss and $β$-Hölder smoothness of the target
by: Ouimet, Frédéric
Published: (2026)

On nonparametric estimation of the interaction function in particle system models
by: Belomestny, Denis, et al.
Published: (2024)

Sharp Convergence Rates of Empirical Unbalanced Optimal Transport for Spatio-Temporal Point Processes
by: Struleva, Marina, et al.
Published: (2025)

Multivariate change estimation for a stochastic heat equation from local measurements
by: Tiepner, Anton, et al.
Published: (2024)

Filtering of partially observed polynomial processes in discrete and continuous time
by: Kallsen, Jan, et al.
Published: (2025)

Local asymptotic normality for discretely observed McKean-Vlasov diffusions
by: Heidari, Akram, et al.
Published: (2025)

The Cost of Adaptation under Differential Privacy: Optimal Adaptive Federated Density Estimation
by: Cai, T. Tony, et al.
Published: (2025)

A convergent scheme for the Bayesian filtering problem based on the Fokker--Planck equation and deep splitting
by: Bågmark, Kasper, et al.
Published: (2024)

Machine Collaboration
by: Liu, Qingfeng, et al.
Published: (2021)

Rank tests for time-varying covariance matrices observed under noise
by: Reiß, Markus, et al.
Published: (2026)

Multiple combined gamma kernel estimations for nonnegative data with Bayesian adaptive bandwidths
by: Somé, Sobom M., et al.
Published: (2022)

Deconvolution of Arbitrary Distribution Functions and Densities
by: Kaiser, Henrik
Published: (2025)

Two approaches to multiple canonical correlation analysis for repeated measures data
by: Górecki, Tomasz, et al.
Published: (2025)

An energy-based deep splitting method for the nonlinear filtering problem
by: Bågmark, Kasper, et al.
Published: (2022)

Adaptive thresholding for wavelet-based nonparametric heteroskedastic variance estimation on the sphere
by: Durastanti, Claudio, et al.
Published: (2026)

Spatio-temporal probabilistic forecast using MMAF-guided learning
by: Bardi, Leonardo, et al.
Published: (2026)

Dirichlet kernel density estimation on the simplex with missing data
by: Daayeb, Hanen, et al.
Published: (2026)

Predictive Inference via Kernel Density Estimates
by: Hilbert, Torey
Published: (2026)

On the Convergence of the ELBO to Entropy Sums
by: Lücke, Jörg, et al.
Published: (2022)

Kernel Density Estimation and Convolution Revisited
by: Tenkorang, Nicholas, et al.
Published: (2025)

A two-sample test for symmetric positive definite matrix distributions using Wishart kernel density estimators
by: Ouimet, Frédéric
Published: (2026)

Breaking the curse of dimensionality in structured density estimation
by: Vandermeulen, Robert A., et al.
Published: (2024)

An operator learning perspective on parameter-to-observable maps
by: Huang, Daniel Zhengyu, et al.
Published: (2024)

Nonparametric estimation of trawl processes: Theory and applications
by: Sauri, Orimar, et al.
Published: (2022)

Comparing Scale Parameter Estimators for Gaussian Process Interpolation with the Brownian Motion Prior: Leave-One-Out Cross Validation and Maximum Likelihood
by: Naslidnyk, Masha, et al.
Published: (2023)

Generative Models with ELBOs Converging to Entropy Sums
by: Warnken, Jan, et al.
Published: (2024)

Bump hunting through density curvature features
by: Chacón, José E., et al.
Published: (2022)