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BNP Course

These are slides and demo notebooks for a short course on BNP given at ENSAE ParisTech in 2016-17-18.

Course material

Complete references are in the slides. Here is a summary of the main references for each lecture:

  • lecture 1: GPs: Chapter 2 of Rasmussen and Williams, Chapter 4 of Orbanz.
  • lecture 2: GPs: Chapters 3 and 5 of Rasmussen and Williams; DPs: Chapter 2 of Orbanz, Chapter 2 of Hjort et al.

Notebooks

Code is Python 3 in jupyter notebooks. Notebooks are numbered in increasing level of course understanding needed. If you are new to Python, I recommend installing the Anaconda distribution. Then simply cd notebooks and run jupyter notebook [name of the notebook]. Alternately, you can visualize the notebooks here on Github, or download the static html versions in the notebooks subdirectory.

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Material for a short graduate course on Bayesian nonparametrics

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