Modular Deep Probabilistic Programming
Modularity is a key feature of deep learning libraries but has not been fully exploited for probabilistic programming. We propose to improve modularity of probabilistic programming language by offering not only plain probabilistic distributions but also sophisticated probabilistic model such as Bayesian non-parametric models as fundamental building blocks... (read more)
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Methods used in the Paper
| METHOD | TYPE | |
|---|---|---|
Gaussian Process
|
Non-Parametric Classification |