572 citations · 657 across the 3 of their papers we have counts for
3 papers
Variational Bayesian Optimal Experimental Design
Adam Foster, Martin Jankowiak, Eli Bingham +4
Bayesian optimal experimental design (BOED) is a principled framework for making efficient use of limited experimental resources. Unfortunately, its applicability is hampered by th…
Pyro: Deep Universal Probabilistic Programming
Eli Bingham, Jonathan P. Chen, Martin Jankowiak +7
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-dimensio…
Deep Amortized Inference for Probabilistic Programs
Daniel Ritchie, Paul Horsfall, Noah D. Goodman
Probabilistic programming languages (PPLs) are a powerful modeling tool, able to represent any computable probability distribution. Unfortunately, probabilistic program inference i…