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 +6 more
doaj +1 more source
Numerical method for impulse control of Piecewise Deterministic Markov Processes [PDF]
, 2011 This paper presents a numerical method to calculate the value function for a general discounted impulse control problem for piecewise deterministic Markov processes.
de Saporta, Benoîte, Dufour, François
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Impulse Control of Piecewise Deterministic Markov Processes
The Annals of Applied Probability, 1995 An optimal impulse control problem for piecewise deterministic Markov processes is considered. This control problem is converted to an equivalent dynamic control problem. Necessary and sufficient conditions for optimality for the former problem are given in terms of the value function of the latter problem.
Dempster, M. A. H., Ye, J. J.
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Average Continuous Control of Piecewise Deterministic Markov Processes
, 2008 This paper deals with the long run average continuous control problem of piecewise deterministic Markov processes (PDMP's) taking values in a general Borel space and with compact action space depending on the state variable.
Costa, O. L. V., Dufour, F.
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Change-point detection for piecewise deterministic Markov processes [PDF]
Automatica, 2018 We consider a change-point detection problem for a simple class of Piecewise Deterministic Markov Processes (PDMPs). A continuous-time PDMP is observed in discrete time and through noise, and the aim is to propose a numerical method to accurately detect both the date of the change of dynamics and the new regime after the change.
Cleynen, Alice, de Saporta, Benoîte
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Optimal Control of Partially Observable Piecewise Deterministic Markov Processes
, 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
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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. +2 more
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Optimizing 3D Bin Packing of Heterogeneous Objects Using Continuous Transformations in SE(3)
Advanced Intelligent Systems, EarlyView.This article presents a method for solving the three‐dimensional bin packing problem for heterogeneous objects using continuous rigid‐body transformations in SE(3). A heuristic optimization framework combines signed‐distance functions, neural network approximations, point‐cloud bin modeling, and physics simulation to ensure feasibility and stability ...
Michele Angelini, Marco Carricato
wiley +1 more source
Optimal choice among a class of nonparametric estimators of the jump rate for piecewise-deterministic Markov processes [PDF]
, 2016 A piecewise-deterministic Markov process is a stochastic process whose behavior is governed by an ordinary differential equation punctuated by random jumps occurring at random times.
Azaïs, Romain, Muller-Gueudin, Aurélie
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Bisimulation for Communicating Piecewise Deterministic Markov Processes (CPDPs) [PDF]
, 2005 CPDPs (Communicating Piecewise Deterministic Markov Processes) can be used for compositional specification of systems from the class of stochastic hybrid processes formed by PDPs (Piecewise Deterministic Markov Processes). We define CPDPs and the composition of CPDPs, and prove that the class of CPDPs is closed under composition.
Strubbe, S.N., van der Schaft, Arjan
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