Results 221 to 230 of about 7,656,330 (292)

An Introduction to Stochastic Deep Learning

WIREs Computational Statistics, Volume 18, Issue 3, September 2026.
The stochastic neural network, formulated as a composition of linear, logistic, and nonlinear regression modules, serves both as a deep learning model and as an analytical device for studying the properties of deep learning. It broadens deep learning beyond prediction‐oriented function approximation into a richer framework for statistical inference ...
Faming Liang
wiley   +1 more source

Singularity in nonlinear systems: differential inclusion model for the standard and transformed fractional pantograph equation. [PDF]

Sci Rep
Mobayen S, Ghaderi M, Shabibi M, Parvaneh Masiha H, Rezapour S.   +4 more
europepmc   +1 more source

Detecting Relevant Deviations From the White Noise Assumption for Non‐Stationary Time Series

Journal of Time Series Analysis, Volume 47, Issue 5, Page 998-1012, September 2026.
ABSTRACT We consider the problem of detecting deviations from a white noise assumption in time series. Our approach differs from the numerous methods proposed for this purpose with respect to two aspects. First, we allow for non‐stationary time series. Second, we address the problem that a white noise test is usually not performed because one believes ...
Patrick Bastian
wiley   +1 more source

Nonlinear fractional stochastic delay modeling and computational analysis of herpes simplex virus type II dynamics. [PDF]

Sci Rep
Raza A, Alsulami M, Lampart M, Shafique U.   +3 more
europepmc   +1 more source

Adaptive Estimation for Weakly Dependent Functional Times Series

Journal of Time Series Analysis, Volume 47, Issue 5, Page 1013-1027, September 2026.
ABSTRACT We propose adaptive mean and autocovariance function estimators for stationary functional time series under 𝕃p−m‐approximability assumptions. These estimators are designed to adapt to the regularity of the curves and to accommodate both sparse and dense data designs.
Hassan Maissoro, Valentin Patilea, Myriam Vimond   +2 more
wiley   +1 more source

Large deviations of piecewise-deterministic Markov processes with application to stochastic calcium waves. [PDF]

J Math Biol
Barbet G, MacLaurin J, Silverstein M, Vilanova P.   +3 more
europepmc   +1 more source

Repelled Point Processes With Application to Numerical Integration

Scandinavian Journal of Statistics, Volume 53, Issue 3, Page 1101-1133, September 2026.
ABSTRACT We look at Monte Carlo numerical integration from a stochastic geometry point of view. While crude Monte Carlo estimators relate to linear statistics of a homogeneous Poisson point process (PPP), linear statistics of more regularly spread point processes can yield unbiased estimators with faster‐decaying variance, and thus lower integration ...
Diala Hawat, Gabriel Mastrilli, Rémi Bardenet, Raphaël Lachièze‐Rey   +3 more
wiley   +1 more source

Divergence and Model Adequacy, a Semiparametric Case Study. [PDF]

Entropy (Basel)
Broniatowski M, Moutsouka J.
europepmc   +1 more source

Exponential convergence for ultrafast diffusion equations with log‐concave weights

Bulletin of the London Mathematical Society, Volume 58, Issue 9, September 2026.
Abstract We study the asymptotic behavior of a weighted ultrafast diffusion PDE on the real line, with a log‐concave and log‐lipschitz weight, and prove exponential convergence to equilibrium. This result goes beyond the compact setting studied in Iacobelli [Discrete Contin. Dyn. Syst. 39 (2019), 4929–4943].
Max Fathi, Mikaela Iacobelli
wiley   +1 more source

A neural network model for managing renewable resources with population growth. [PDF]

Sci Rep
Ahmad S, Ahmad I, Alluhaidan AS, ElAffendi MA.   +3 more
europepmc   +1 more source