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dc.contributor.authorMoraes, Alvaro
dc.contributor.authorTempone, Raul
dc.contributor.authorVilanova, Pedro
dc.date.accessioned2017-06-01T10:20:43Z
dc.date.available2017-06-01T10:20:43Z
dc.date.issued2014-01-06
dc.identifier.urihttp://hdl.handle.net/10754/624001
dc.description.abstractMarkovian pure jump processes can model many phenomena, e.g. chemical reactions at molecular level, protein transcription and translation, spread of epidemics diseases in small populations and in wireless communication networks, among many others. In this work [6] we present a novel multilevel algorithm for the Chernoff-based hybrid tauleap algorithm. This variance reduction technique allows us to: (a) control the global exit probability of any simulated trajectory, (b) obtain accurate and computable estimates for the expected value of any smooth observable of the process with minimal computational work.
dc.subjectSampling
dc.titleMultilevel Hybrid Chernoff Tau-Leap
dc.typePoster
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.conference.dateJanuary 6-10, 2014
dc.conference.nameAdvances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2014)
dc.conference.locationKAUST
kaust.personMoraes, Alvaro
kaust.personTempone, Raul
kaust.personVilanova, Pedro
refterms.dateFOA2018-06-13T15:55:14Z


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