no code implementations • 27 Nov 2024 • Patrick Mineault, Niccolò Zanichelli, Joanne Zichen Peng, Anton Arkhipov, Eli Bingham, Julian Jara-Ettinger, Emily Mackevicius, Adam Marblestone, Marcelo Mattar, Andrew Payne, Sophia Sanborn, Karen Schroeder, Zenna Tavares, Andreas Tolias
As AI systems become increasingly powerful, the need for safe AI has become more pressing.
no code implementations • 29 Feb 2024 • Raj Agrawal, Sam Witty, Andy Zane, Eli Bingham
We prove that MC-EIF is consistent, and that estimators using MC-EIF achieve optimal $\sqrt{N}$ convergence rates.
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.
1 code implementation • NeurIPS 2019 • Adam Foster, Martin Jankowiak, Eli Bingham, Paul Horsfall, Yee Whye Teh, Tom Rainforth, Noah Goodman
Bayesian optimal experimental design (BOED) is a principled framework for making efficient use of limited experimental resources.
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.
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.