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Pyro is a probabilistic programming language built on Python as a platform for developing advanced probabilistic models in AI research.
Church: A Language for Generative Models
Noah D. Goodman, Vikash K. Mansinghka, Daniel Roy, Keith Bonawitz, and Joshua B. Tenenbaum · 2008
Earlier work this paper cites.
Lightweight Implementations of Probabilistic Programming Languages via Transformational Compilation
David Wingate, Andreas Stuhlmüller, and Noah Goodman · 2011
Earlier work this paper cites.
Handlers in Action
Ohad Kammar, Sam Lindley, and Nicolas Oury · 2013
Earlier work this paper cites.
The Design and Implementation of Probabilistic Programming Languages
Noah D Goodman and Andreas Stuhlmüller · 2014
Earlier work this paper cites.
The No-U-turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
Matthew D. Hoffman and Andrew Gelman · 2014
Earlier work this paper cites.
Auto-encoding Variational Bayes
Diederik P Kingma and Max Welling · 2014
Earlier work this paper cites.
Probabilistic machine learning and artificial intelligence
Zoubin Ghahramani · 2015
Cited alongside, same era.
Improved Variational Inference with Inverse Autoregressive Flow
Diederik P Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever, and Max Welling · 2016
Cited alongside, same era.
Design and Implementation of Probabilistic Programming Language Anglican
David Tolpin, Jan-Willem van de Meent, Hongseok Yang, and Frank Wood · 2016
Cited alongside, same era.
Stan: A Probabilistic Programming Language
Bob Carpenter, Andrew Gelman, Matthew D. Hoffman, Daniel Lee, Ben Goodrich, Michael Betancourt, Marcus Brubaker, Jiqiang Guo, Peter Li, and Allen Riddell · 2017
Cited alongside, same era.
Joshua V. Dillon, Ian Langmore, Dustin Tran, Eugene Brevdo, Srinivas Vasudevan, Dave Moore, Brian Patton, Alex Alemi, Matt Hoffman, and Rif A. Saurous · 2017
Cited alongside, same era.
Structured Inference Networks for Nonlinear State Space Models
Rahul G Krishnan, Uri Shalit, and David Sontag · 2017
Later among the works it cites.
Learning Disentangled Representations with Semi-Supervised Deep Generative Models
N. Siddharth, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah D. Goodman, Pushmeet Kohli, Frank Wood, and Philip Torr · 2017
Later among the works it cites.
Deep Probabilistic Programming
Dustin Tran, Matthew D. Hoffman, Rif A. Saurous, Eugene Brevdo, Kevin Murphy, and David M. Blei · 2017
Later among the works it cites.
Turing: A Language for Flexible Probabilistic Inference
Hong Ge, Kai Xu, and Zoubin Ghahramani · 2018
Closest in time.
Probabilistic Programming with Programmable Inference
Vikash K. Mansinghka, Ulrich Schaechtle, Shivam Handa, Alexey Radul, Yutian Chen, and Martin Rinard · 2018
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