JMLR Journal 2019 Journal Article
Pyro: Deep Universal Probabilistic Programming
- Eli Bingham
- Jonathan P. Chen
- Martin Jankowiak
- Fritz Obermeyer
- Neeraj Pradhan
- Theofanis Karaletsos
- Rohit Singh
- Paul Szerlip
Pyro is a probabilistic programming language built on Python as a platform for developing advanced probabilistic models in AI research. To scale to large data sets 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. [abs] [ pdf ][ bib ] [ code ] © JMLR 2019. ( edit, beta )