Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Przybylowicz, Pawel"'
Autor:
Przybyłowicz, Paweł, Sobieraj, Michał
In this paper, we investigate the problem of strong approximation of the solution of SDEs in the case when the drift coefficient is given in the integral form. Such drift often appears when analyzing stochastic dynamics of optimization procedures in
Externí odkaz:
http://arxiv.org/abs/2405.20481
We randomize the implicit two-stage Runge-Kutta scheme to improve the rate of convergence (compared to a deterministic scheme) and stability of the approximate solution (contrasted to the solution generated by the explicit scheme). For stability anal
Externí odkaz:
http://arxiv.org/abs/2404.19059
In this paper we investigate the existence, uniqueness and approximation of solutions of delay differential equations (DDEs) with the right-hand side functions $f=f(t,x,z)$ that are Lipschitz continuous with respect to $x$ but only H\"older continuou
Externí odkaz:
http://arxiv.org/abs/2401.11658
Autor:
Kałuża, Andrzej, Morkisz, Paweł M., Mulewicz, Bartłomiej, Przybyłowicz, Paweł, Wiącek, Martyna
We present a novel deep learning method for estimating time-dependent parameters in Markov processes through discrete sampling. Departing from conventional machine learning, our approach reframes parameter approximation as an optimization problem usi
Externí odkaz:
http://arxiv.org/abs/2312.08493
This paper focuses on analyzing the error of the randomized Euler algorithm when only noisy information about the coefficients of the underlying stochastic differential equation (SDE) and the driving Wiener process is available. Two classes of distur
Externí odkaz:
http://arxiv.org/abs/2307.04718
On approximation of solutions of stochastic delay differential equations via randomized Euler scheme
We investigate existence, uniqueness and approximation of solutions to stochastic delay differential equations (SDDEs) under Carath\'eodory-type drift coefficients. Moreover, we also assume that both drift $f=f(t,x,z)$ and diffusion $g=g(t,x,z)$ coef
Externí odkaz:
http://arxiv.org/abs/2306.08926
In this note we prove sharp lower error bounds for numerical methods for jump-diffusion stochastic differential equations (SDEs) with discontinuous drift. We study the approximation of jump-diffusion SDEs with non-adaptive as well as jump-adapted app
Externí odkaz:
http://arxiv.org/abs/2303.05945
We investigate the error of the randomized Milstein algorithm for solving scalar jump-diffusion stochastic differential equations. We provide a complete error analysis under substantially weaker assumptions than known in the literature. In case the j
Externí odkaz:
http://arxiv.org/abs/2212.00411
We present the first higher-order approximation scheme for solutions of jump-diffusion stochastic differential equations with discontinuous drift. For this transformation-based jump-adapted quasi-Milstein scheme we prove $L^p$-convergence order 3/4.
Externí odkaz:
http://arxiv.org/abs/2211.08739
We investigate error of the Euler scheme in the case when the right-hand side function of the underlying ODE satisfies nonstandard assumptions such as local one-sided Lipschitz condition and local H\"older continuity. Moreover, we assume two cases in
Externí odkaz:
http://arxiv.org/abs/2209.07482