Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Sikorski, Alexander"'
Autor:
Sikorski, Alexander, Heida, Martin
The computation of Voronoi Diagrams, or their dual Delauney triangulations is difficult in high dimensions. In a recent publication Polianskii and Pokorny propose an iterative randomized algorithm facilitating the approximation of Voronoi tesselation
Externí odkaz:
http://arxiv.org/abs/2405.10050
Markov processes serve as foundational models in many scientific disciplines, such as molecular dynamics, and their simulation forms a common basis for analysis. While simulations produce useful trajectories, obtaining macroscopic information directl
Externí odkaz:
http://arxiv.org/abs/2404.10523
Estimating the rate of rare conformational changes in molecular systems is one of the goals of Molecular Dynamics simulations. In the past decades, a lot of progress has been done in data-based approaches towards this problem. In contrast, model-base
Externí odkaz:
http://arxiv.org/abs/2311.09779
For stochastic diffusion processes the dominant eigenfunctions of the corresponding Koopman operator contain important information about the slow-scale dynamics, that is, about the location and frequency of rare events. In this article, we reformulat
Externí odkaz:
http://arxiv.org/abs/2301.00065
The Robust Perron Cluster Analysis (PCCA+) has become a popular spectral clustering algorithm for coarse-graining transition matrices of nearly decomposable Markov chains with transition states. Originally developed for reversible Markov chains, the
Externí odkaz:
http://arxiv.org/abs/2206.14537
Publikováno v:
In Journal of Computational and Applied Mathematics July 2024 444
Publikováno v:
Journal of Chemical Physics; 3/14/2024, Vol. 160 Issue 10, p1-15, 15p
Modern methods of simulating molecular systems are based on the mathematical theory of Markov operators with a focus on autonomous equilibrated systems. However, non-autonomous physical systems or non-autonomous simulation processes are becoming more
Externí odkaz:
http://arxiv.org/abs/2008.04624
One of the main goals of mathematical modeling in systems medicine related to medical applications is to obtain patient-specific parameterizations and model predictions. In clinical practice, however, the number of available measurements for single p
Externí odkaz:
http://arxiv.org/abs/1612.01403
When dealing with Bayesian inference the choice of the prior often remains a debatable question. Empirical Bayes methods offer a data-driven solution to this problem by estimating the prior itself from an ensemble of data. In the nonparametric case,
Externí odkaz:
http://arxiv.org/abs/1612.00064