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arXiv · 1810.09538

Pyro: Deep Universal Probabilistic Programming

Eli Bingham·Jonathan P. Chen·Martin Jankowiak·Fritz Obermeyer·Neeraj Pradhan·Theofanis Karaletsos·Rohit Singh·Paul Szerlip·Paul Horsfall·Noah D. Goodman
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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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BibTeXRIS

Eli Bingham, Jonathan P. Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul Szerlip, Paul Horsfall, Noah D. Goodman. 2018-10-18. Pyro: Deep Universal Probabilistic Programming. https://arxiv.org/abs/1810.09538

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