Results 1 to 10 of about 26,127 (206)

Optimal Control of Partially Observable Piecewise Deterministic Markov Processes

SIAM Journal on Control and Optimization, 2018
In this paper we consider a control problem for a Partially Observable Piecewise Deterministic Markov Process of the following type: After the jump of the process the controller receives a noisy signal about the state and the aim is to control the ...
Bäuerle, Nicole, Lange, Dirk
core   +3 more sources

Simulating the formation of keratin filament networks by a piecewise-deterministic Markov process.

Journal of Theoretical Biology, 2009
Keratin intermediate filament networks are part of the cytoskeleton in epithelial cells. They were found to regulate viscoelastic properties and motility of cancer cells.
M. Beil, S. Lück, F. Fleischer, Stéphanie Portet, W. Arendt, V. Schmidt   +5 more
semanticscholar   +3 more sources

Multiscale Piecewise Deterministic Markov Process in Infinite Dimension: Central Limit Theorem and Langevin Approximation [PDF]

, 2012
In [20], the authors addressed the question of the averaging of a slow-fast Piecewise Deterministic Markov Process (PDMP) in infinite dimension. In the present paper, we carry on and complete this work by the mathematical analysis of the fluctuation of ...
A. Genadot, M. Thieullen
semanticscholar   +1 more source

WASABI: a dynamic iterative framework for gene regulatory network inference

BMC Bioinformatics, 2019
Background Inference of gene regulatory networks from gene expression data has been a long-standing and notoriously difficult task in systems biology.
Arnaud Bonnaffoux, Ulysse Herbach, Angélique Richard, Anissa Guillemin, Sandrine Gonin-Giraud, Pierre-Alexis Gros, Olivier Gandrillon   +6 more
doaj   +1 more source

A probabilistic view on the deterministic mutation-selection equation: dynamics, equilibria, and ancestry via individual lines of descent

, 2018
We reconsider the deterministic haploid mutation-selection equation with two types. This is an ordinary differential equation that describes the type distribution (forward in time) in a population of infinite size.
Baake, Ellen, Cordero, Fernando, Hummel, Sebastian   +2 more
core   +1 more source

On the connection between exponential ergodicity of a piecewise deterministic Markov process and the chain given by its post-jump locations

, 2020
The aim of this paper is to derive the exponential ergodicity in the Wasserstein distance for a piecewise-deterministic Markov process (PDMP), being typically encountered in biological models, defined via interpolation of some discrete-time Markov chain.
D. Czapla, Katarzyna Horbacz, Hanna Wojewódka-Ścia̧żko   +2 more
semanticscholar   +1 more source

Piecewise Deterministic Markov Processes for Continuous-Time Monte Carlo [PDF]

Statistical Science, 2016
Recently, there have been conceptually new developments in Monte Carlo methods through the introduction of new MCMC and sequential Monte Carlo (SMC) algorithms which are based on continuous-time, rather than discrete-time, Markov processes.
P. Fearnhead, J. Bierkens, M. Pollock, G. Roberts   +3 more
semanticscholar   +1 more source

Markov branching processes with disasters: extinction, survival and duality to p-jump processes

, 2019
A $p$-jump process is a piecewise deterministic Markov process with jumps by a factor of $p$. We prove a limit theorem for such processes on the unit interval.
Hermann, F., Pfaffelhuber, P.
core   +1 more source

Stochastic Representations of Ion Channel Kinetics and Exact Stochastic Simulation of Neuronal Dynamics [PDF]

, 2014
In this paper we provide two representations for stochastic ion channel kinetics, and compare the performance of exact simulation with a commonly used numerical approximation strategy.
Anderson, David F., Ermentrout, Bard, Thomas, Peter J.   +2 more
core   +3 more sources

On the continuous dependence of the stationary distribution of a piecewise deterministic Markov process on its jump intensity

, 2020
We examine a piecewise deterministic Markov process, whose whole randomness stems from the jumps, which occur at the random time points according to a Poisson process, and whose post-jump locations are attained by randomly selected transformations of the
D. Czapla, S. Hille, Katarzyna Horbacz, Hanna Wojewódka-Ścia̧żko   +3 more
semanticscholar   +1 more source