O. Mokliachuk

collaborators

5 papers

math.ST2026

Quasi-Banach spaces of random variables and stochastic processes

Yuriy Kozachenko, Yuriy Mlavets, Oleksandr Mokliachuk

This book develops the theory of quasi-Banach $K_{σ}$ -spaces $F_{ψ} (Ω)$ , $F_{ψ}^{*} (Ω)$ , and $D_{V, W} (Ω)$ of random variables and stochastic processes, extending the clas…

eess.IV2026

Learning to Recorrupt: Noise Distribution Agnostic Self-Supervised Image Denoising

Brayan Monroy, Jorge Bacca, Julián Tachella

Self-supervised image denoising methods have traditionally relied on either architectural constraints or specialized loss functions that require prior knowledge of the noise distri…

math.PR2025

Modelling with given reliability and accuracy in the space $L_{p} (T)$ of stochastic processes from $S u b_{φ} (Ω)$ decomposable in series with independent elements

Oleksandr Mokliachuk

Models that approximate stochastic processes from $S u b_{φ} (Ω)$ with given reliability and accuracy in $L_{p} (T)$ for some given $φ (t)$ are considered. We also study construction of mod…

math.ST2025

Estimation of accuracy and reliability of models of $φ$ -sub-Gaussian stochastic processes in $C (T)$ spaces

Oleksandr Mokliachuk

At present, in the theory of stochastic process modeling a problem of assessment of reliability and accuracy of stochastic process model in $C (T)$ space wasn't studied for the case…

math.ST2025

Modeling of stochastic processes in $L_{p} (T)$ using orthogonal polynomials

Oleksandr Mokliachuk

In this paper, models that approximate stochastic processes from the space $S u b_{φ} (Ω)$ with given reliability and accuracy in $L_{p} (T)$ are considered for some specific functions $φ(…

Quasi-Banach spaces of random variables and stochastic processes

Learning to Recorrupt: Noise Distribution Agnostic Self-Supervised Image Denoising

Modelling with given reliability and accuracy in the space Lp​(T) of stochastic processes from Subφ​(Ω) decomposable in series with independent elements

Estimation of accuracy and reliability of models of φ-sub-Gaussian stochastic processes in C(T) spaces

Modeling of stochastic processes in Lp​(T) using orthogonal polynomials

Modelling with given reliability and accuracy in the space $L_{p} (T)$ of stochastic processes from $S u b_{φ} (Ω)$ decomposable in series with independent elements

Estimation of accuracy and reliability of models of $φ$ -sub-Gaussian stochastic processes in $C (T)$ spaces

Modeling of stochastic processes in $L_{p} (T)$ using orthogonal polynomials