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examples/mixture_models/dp_mix.ipynb

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"\n",
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" $$P = \\sum_{i = 1}^\\infty \\mu_i \\delta_{\\omega_i} \\sim \\textrm{DP}(\\alpha, P_0).$$\n",
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" \n",
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"[Suggested Further Reading]: (http://mlg.eng.cam.ac.uk/tutorials/07/ywt.pdf) and {cite:p}`teh2010dirichletprocess` for a brief introduction to other flavours of Dirichlet Processes, and their applications.\n",
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"[Suggested Further Reading]: (http://mlg.eng.cam.ac.uk/tutorials/07/ywt.pdf) and {cite:t}`teh2010dirichletprocess` for a brief introduction to other flavours of Dirichlet Processes, and their applications.\n",
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"\n",
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"We can use the stick-breaking process above to easily sample from a Dirichlet process in Python. For this example, $\\alpha = 2$ and the base distribution is $N(0, 1)$."
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examples/references.bib

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@@ -162,7 +162,7 @@ @misc{nowicka2016drimseq
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month={Dec}
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}
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@inproceedings{roy2008npbayes,
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@article{roy2008npbayes,
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title={A stochastic programming perspective on nonparametric Bayes},
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author={Daniel M. Roy, Vikash Mansinghka, Noah Goodman and Joshua Tenenbaum},
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journal={International Conference on Machine Learning: Workshop on Nonparametric Bayesian},

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