[Uber Open Summit 2018] Pyro: Deep Probabilistic Programming

Pyro is a deep probabilistic programming language built on PyTorch, a GPU-accelerated deep learning framework. Developed at Uber AI Labs by Noah Goodman and team, Pyro is used as a platform for research in modern Bayesian machine learning, where deep neural networks can be used both in models and in inference. To scale to large datasets and high-dimensional models, Pyro uses stochastic variational inference algorithms and probability distributions built on top of PyTorch. The Pyro team works closely with the PyTorch team and many open source collaborators to create a rich, stable toolset for probabilistic machine learning research. During this Uber Open Summit 2018 tech talk, AI Labs' JP Chen and Fritz Obermeyer discuss how to use this tool and contribute to Pyro's growing open source AI ecosystem. Learn more about Uber Open Source: https://uber.github.io/