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Non-parametric Bayesian Models

Models used in Bayesian inference that do not commit a prior distribution to a particular number of parameters; instead the data is allowed to dictate how many parameters there are. Possible overfitting is prevented by integrating out all parameters and latent variables.

Non-parametric Bayesian Models

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