3260 papers • 126 benchmarks • 313 datasets
Probabilistic programming languages are designed to describe probabilistic models and then perform inference in those models. PPLs are closely related to graphical models and Bayesian networks, but are more expressive and flexible. ( Image credit: Michael Betancourt )
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