1 citations · 1 across the 5 of their papers we have counts for
5 papers
milearn: A Python Package for Multi-Instance Machine Learning
Dmitry Zankov, Pavlo Polishchuk, Michal Sobieraj +1
We introduce milearn, a Python package for multi-instance learning (MIL) that follows the familiar scikit-learn fit/predict interface while providing a unified framework for both c…
On the randomized Euler scheme for SDEs with integral-form drift
Paweł Przybyłowicz, Michał Sobieraj
In this paper, we investigate the problem of strong approximation of the solutions of stochastic differential equations (SDEs) when the drift coefficient is given in integral form.…
On the randomized Euler algorithm under inexact information
Marcin Baranek, Andrzej Kałuża, Paweł M. Morkisz +2
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 (S…
A multilevel Monte Carlo algorithm for SDEs driven by countably dimensional Wiener process and Poisson random measure
Michał Sobieraj
In this paper, we investigate the properties of standard and multilevel Monte Carlo methods for weak approximation of solutions of stochastic differential equations (SDEs) driven b…
On automatic calibration of the SIRD epidemiological model for COVID-19 data in Poland
Piotr Błaszczyk, Konrad Klimczak, Adam Mahdi +4
We propose a novel methodology for estimating the epidemiological parameters of a modified SIRD model (acronym of Susceptible, Infected, Recovered and Deceased individuals) and per…