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  1. Nicolas Chopin is a researcher and teacher in Bayesian computation, Monte Carlo methods, and machine learning. He is the author of a book on Sequential Monte Carlo and the developer of a python library for Bayesian inference.

    • Home

      Nicolas Chopin. GitHub Mastodon ORCID Google Scholar...

    • Papers

      Chopin, N., and Pelgrin, F. Bayesian inference and state...

    • Book

      Nicolas Chopin and Omiros Papaspiliopoulos. Available here....

    • Software

      Actively developed. particles: Sequential Monte Carlo python...

    • Teaching

      ENSAE. Introduction aux processus: poly simulation and Monte...

    • CV

      Nicolas Chopin Professor of data sciences ENSAE 5 avenue...

    • Blog

      Nicolas Chopin Quantum workers in Bernoulli factories...

  2. Nicolas Chopin (in Polish: Mikołaj Chopin; 15 April 1771 – 3 May 1844) was a teacher of the French language in Partitioned Poland, and father of Polish composer Frédéric Chopin.

  3. Articles 1–20. ‪Professor of Statistics, ENSAE (Institut Polytechnique de Paris)‬ - ‪‪Cited by 11,172‬‬ - ‪Statistics‬ - ‪Bayesian Stastistics‬ - ‪Bayesian Machine Learning Monte Carlo methods‬ - ‪Bayesian computation‬ - ‪particle filtering‬.

  4. sites.google.com › site › nicolaschopinstatisticianNicolas Chopin - Google Sites

    I am a professor of Statistics at the ENSAE since 2006. Before that I was a lecturer at the Department of Mathematics of Bristol University (UK). My main research interest is SMC...

  5. Nicolas Chopin Professor of data sciences ENSAE 5 avenue Henry Le Chatelier 91764 Palaiseau CedexFRANCE — +33 1 41 17 65 22 # nicolas.chopin@ensae.fr ‡ https://nchopin.github.io/ Experience Sept. 2006– to date Professor of data sciences, ENSAE, IPP, Palaiseau, FRANCE 2003–2006 Lecturer in Statistics, Bristol University, UK

  6. Nicolas Chopin is a Professor of Data Sciences at the ENSAE since 2006. Before that he was a lecturer at Bristol University (2003-2006).

  7. Higher-order stochastic integration through cubic stratification. We propose two novel unbiased estimators of the integral $\int_ { [0,1]^ {s}}f (u) du$ for a function $f$, which depend on a ...