Pyro: Deep Universal Probabilistic Programming
Eli Bingham(Uber AI (United States)), Jonathan P. Chen(Uber AI (United States)), Martin Jankowiak(Uber AI (United States)), Fritz Obermeyer(Uber AI (United States)), Neeraj Pradhan(Uber AI (United States)), Theofanis Karaletsos(Uber AI (United States)), Rohit Singh(Uber AI (United States)), Paul Szerlip(Uber AI (United States)), Paul Horsfall(Stanford University), Noah D. Goodman(Stanford University)
Cited by 591Open Access
Abstract
Pyro is a probabilistic programming language built on Python as a platform for developing advanced probabilistic models in AI research. To scale to large datasets and high-dimensional models, Pyro uses stochastic variational inference algorithms and probability distributions built on top of PyTorch, a modern GPU-accelerated deep learning framework. To accommodate complex or model-specific algorithmic behavior, Pyro leverages Poutine, a library of composable building blocks for modifying the behavior of probabilistic programs.
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