Support and influence analysis for visualizing posteriors of probabilistic programs
نویسنده
چکیده
A common way to interpret the results of any computational model is to visualize its output. For probabilistic programming, this often means visualizing a posterior probability distribution. The webppl language has a visualization library called webppl-viz that facilitates this process. A useful feature of webppl-viz is that it does some amount of automatic visualization—the user simply passes in the posterior they wish to inspect and the library tries to construct a useful visual representation of it. For instance, consider this posterior:
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