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 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](https://www.pdfsearch.io/img/e122e812a95d5e34c6db167ca74c9598.jpg) | Add to Reading ListSource URL: qav.comlab.ox.ac.ukLanguage: English - Date: 2017-03-10 09:53:57
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2![Monte Carlo Markov Chain Algorithms for Sampling Strongly Rayleigh Distributions and Determinantal Point Processes Nima Anari ∗ Monte Carlo Markov Chain Algorithms for Sampling Strongly Rayleigh Distributions and Determinantal Point Processes Nima Anari ∗](https://www.pdfsearch.io/img/1120139dd4f826b4bb17903c49d12b4e.jpg) | Add to Reading ListSource URL: nimaanari.comLanguage: English - Date: 2018-07-31 20:03:09
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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 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](https://www.pdfsearch.io/img/379010fcf0036382077112c91c603489.jpg) | Add to Reading ListSource URL: www1.isti.cnr.itLanguage: English - Date: 2012-04-26 13:45:45
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4![ODE approximations to some Markov chain models Perla Sousi January 13, 2009 ODE approximations to some Markov chain models Perla Sousi January 13, 2009](https://www.pdfsearch.io/img/f7529ffecfdbc3e2ac7024925b4f3bbd.jpg) | Add to Reading ListSource URL: www.statslab.cam.ac.ukLanguage: English - Date: 2010-11-09 23:45:53
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5![Compiling Markov Chain Monte Carlo Algorithms for Probabilistic Modeling Daniel Huang Jean-Baptiste Tristan Compiling Markov Chain Monte Carlo Algorithms for Probabilistic Modeling Daniel Huang Jean-Baptiste Tristan](https://www.pdfsearch.io/img/a5bba0c80486d6dc3fd54b908423ef0d.jpg) | Add to Reading ListSource URL: danehuang.github.ioLanguage: English - Date: 2017-05-24 19:52:40
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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 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](https://www.pdfsearch.io/img/5fbafb80459f8cd832b5c59bbb5392f6.jpg) | Add to Reading ListSource URL: nitro.biosci.arizona.eduLanguage: English - Date: 2008-10-18 08:48:14
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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 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](https://www.pdfsearch.io/img/9019683ab548f02234e7b00a6b67392a.jpg) | Add to Reading ListSource URL: www.lbreyer.comLanguage: English - Date: 2012-10-12 09:09:02
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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 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](https://www.pdfsearch.io/img/ed0a274bf82f5ae39e56e8618d36bd1f.jpg) | Add to Reading ListSource URL: www.stanfordphd.comLanguage: English - Date: 2018-02-16 02:18:47
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9![Compiling Markov Chain Monte Carlo Algorithms for Probabilistic Modeling Daniel Huang Jean-Baptiste Tristan Compiling Markov Chain Monte Carlo Algorithms for Probabilistic Modeling Daniel Huang Jean-Baptiste Tristan](https://www.pdfsearch.io/img/f23e32e517278b470e96c856e36d8bb3.jpg) | Add to Reading ListSource URL: jtristan.github.ioLanguage: English - Date: 2018-06-24 11:22:27
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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 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](https://www.pdfsearch.io/img/e16796f6f6850ba4dbabeef4c86735fa.jpg) | Add to Reading ListSource URL: nitro.biosci.arizona.eduLanguage: English - Date: 2013-06-13 20:34:34
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