Corpus ID: 53038373

Pyro: Deep Universal Probabilistic Programming

@article{Bingham2019PyroDU,
  title={Pyro: Deep Universal Probabilistic Programming},
  author={Eli Bingham and Jonathan P. Chen and Martin Jankowiak and Fritz Obermeyer and Neeraj Pradhan and Theofanis Karaletsos and Rohit Singh and Paul A. Szerlip and Paul Horsfall and Noah D. Goodman},
  journal={ArXiv},
  year={2019},
  volume={abs/1810.09538}
}
  • Eli Bingham, Jonathan P. Chen, +7 authors Noah D. Goodman
  • Published 2019
  • Mathematics, Computer Science
  • ArXiv
  • 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… CONTINUE READING

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