1 code implementation • 23 Oct 2019 • Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Du Phan, Jonathan P. Chen
It is a significant challenge to design probabilistic programming systems that can accommodate a wide variety of inference strategies within a unified framework.
no code implementations • 8 Feb 2019 • Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Justin Chiu, Neeraj Pradhan, Alexander Rush, Noah Goodman
To exploit efficient tensor algebra in graphs with plates of variables, we generalize undirected factor graphs to plated factor graphs and variable elimination to a tensor variable elimination algorithm that operates directly on plated factor graphs.
no code implementations • 21 Nov 2018 • Jonathan P. Chen, Fritz Obermeyer, Vladimir Lyapunov, Lionel Gueguen, Noah D. Goodman
Our algorithm outperforms our current production baseline based on k-means clustering.
1 code implementation • 18 Oct 2018 • Eli Bingham, Jonathan P. Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul Szerlip, Paul Horsfall, Noah D. Goodman
Pyro is a probabilistic programming language built on Python as a platform for developing advanced probabilistic models in AI research.
no code implementations • ICML 2018 • Martin Jankowiak, Fritz Obermeyer
We observe that gradients computed via the reparameterization trick are in direct correspondence with solutions of the transport equation in the formalism of optimal transport.
no code implementations • 22 Feb 2014 • Fritz Obermeyer, Jonathan Glidden, Eric Jonas
This new algorithm learns nonparametric latent structure over a growing and constantly churning subsample of training data, where the portion of data subsampled can be interpreted as the inverse temperature beta(t) in an annealing schedule.