Markov chain

Results: 2175



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1

Designing Robust Software Systems through Parametric Markov Chain Synthesis ˇ ska† , Simos Gerasimou∗ , Marta Kwiatkowska‡ and Nicola Paoletti§ Radu Calinescu∗ , Milan Ceˇ ∗ Department of Computer Science, U

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Source URL: qav.comlab.ox.ac.uk

Language: English - Date: 2017-03-10 09:53:57
    2

    Monte Carlo Markov Chain Algorithms for Sampling Strongly Rayleigh Distributions and Determinantal Point Processes Nima Anari ∗

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    Source URL: nimaanari.com

    Language: English - Date: 2018-07-31 20:03:09
      3

      Mean field and fluid approaches to Markov chain analysis Jeremy T. Bradley ∗ Department of Computing, Imperial College London, UK Representing the explicit state space of performance models has inheren

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      Source URL: www1.isti.cnr.it

      Language: English - Date: 2012-04-26 13:45:45
        4

        ODE approximations to some Markov chain models Perla Sousi January 13, 2009

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        Source URL: www.statslab.cam.ac.uk

        Language: English - Date: 2010-11-09 23:45:53
          5

          Compiling Markov Chain Monte Carlo Algorithms for Probabilistic Modeling Daniel Huang Jean-Baptiste Tristan

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          Source URL: danehuang.github.io

          Language: English - Date: 2017-05-24 19:52:40
            6

            Appendix 3 Markov Chain Monte Carlo and Gibbs Sampling A constant them in the development of statistics has been the search for justifications for what statisticians do — BlascoDraft version 12 September 2008

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            Source URL: nitro.biosci.arizona.edu

            Language: English - Date: 2008-10-18 08:48:14
              7

              A NEW METHOD FOR COUPLING RANDOM FIELDS L.A. BREYER AND G.O. ROBERTS Abstract. Given a Markov chain, a stochastic flow which simultaneously constructs sample paths started at each possible initial value can be constructe

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              Source URL: www.lbreyer.com

              Language: English - Date: 2012-10-12 09:09:02
                8

                TASK The arrival of new customers is modeled in the following way. Let X_t be a continuous time Markov chain, which occupies state i at time 0. Conditional on all the future dynamics of X_t, process N_t is a Poisson proc

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                Source URL: www.stanfordphd.com

                Language: English - Date: 2018-02-16 02:18:47
                  9

                  Compiling Markov Chain Monte Carlo Algorithms for Probabilistic Modeling Daniel Huang Jean-Baptiste Tristan

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                  Source URL: jtristan.github.io

                  Language: English - Date: 2018-06-24 11:22:27
                    10

                    Appendix 3 Markov Chain Monte Carlo and Gibbs Sampling Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise – Tukey

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                    Source URL: nitro.biosci.arizona.edu

                    Language: English - Date: 2013-06-13 20:34:34
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