Evolution Equations on Co-evolving Graphs: Long-Time Behaviour and the Graph-Continuity Equation. [PDF]
Carrillo JA, Esposito A, Mikolás L.
europepmc +1 more source
Fractal–fractional model for analysis of tuberculosis infection using Ethiopia incidence data
Abstract In this study, a fractional‐order SEIuITR $SE{I}_{u}ITR$ model was proposed to examine the transmission of tuberculosis (TB) in the community. The proposed model was rigorously examined for well‐posedness. The basic reproduction number was also derived, and the disease‐free equilibrium was obtained.
Kumama Regassa Cheneke +2 more
wiley +1 more source
Large deviations of piecewise-deterministic Markov processes with application to stochastic calcium waves. [PDF]
Barbet G +3 more
europepmc +1 more source
Squeezed‐State Semi‐Device‐Independent Quantum Randomness Generation
Semi‐device‐independent quantum randomness is certified for squeezed‐coherent binary states using only their trusted overlap and the observed homodyne error. Including the deterministic extremes of the full binary‐qubit POVM gives the correct closed‐form Shannon rate.
Hamid Tebyanian
wiley +1 more source
An Entropy-Based Framework for Hybrid Coalitions in Game Theory-Part I: Human Arbitration. [PDF]
Sepúlveda-Fontaine SA, Amigó JM.
europepmc +1 more source
An Introduction to Stochastic Deep Learning
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
Nonlinear fractional stochastic delay modeling and computational analysis of herpes simplex virus type II dynamics. [PDF]
Raza A +3 more
europepmc +1 more source
Detecting Relevant Deviations From the White Noise Assumption for Non‐Stationary Time Series
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
Searching in Euclidean Spaces with Predictions. [PDF]
Cabello S, Giannopoulos P.
europepmc +1 more source
Adaptive Estimation for Weakly Dependent Functional Times Series
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 +2 more
wiley +1 more source

