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Automated learning with a probabilistic programming language: Birch

2 October 2018

Papers citing "Automated learning with a probabilistic programming language: Birch"

23 / 23 papers shown

Title
Pyro: Deep Universal Probabilistic Programming Eli Bingham Jonathan P. Chen M. Jankowiak F. Obermeyer Neeraj Pradhan Theofanis Karaletsos Rohit Singh Paul A. Szerlip Paul Horsfall Noah D. Goodman BDL GP 158 1,057 0 18 Oct 2018
Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs Lawrence M. Murray Daniel Lundén J. Kudlicka David Broman Thomas B. Schon 52 60 0 25 Aug 2017
Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo Thomas B. Schon Andreas Svensson Lawrence M. Murray Fredrik Lindsten 54 41 0 07 Mar 2017
Edward: A library for probabilistic modeling, inference, and criticism Dustin Tran A. Kucukelbir Adji Bousso Dieng Maja R. Rudolph Dawen Liang David M. Blei 93 300 0 31 Oct 2016
The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data J. Bierkens Paul Fearnhead Gareth O. Roberts 96 233 0 11 Jul 2016
Data-driven Sequential Monte Carlo in Probabilistic Programming Yura N. Perov T. Le Frank Wood BDL 37 7 0 14 Dec 2015
The Correlated Pseudo-Marginal Method George Deligiannidis Arnaud Doucet M. Pitt 110 101 0 16 Nov 2015
The Bouncy Particle Sampler: A Non-Reversible Rejection-Free Markov Chain Monte Carlo Method Alexandre Bouchard-Côté Sebastian J. Vollmer Arnaud Doucet 98 237 0 08 Oct 2015
A New Approach to Probabilistic Programming Inference Frank Wood Jan-Willem van de Meent Vikash K. Mansinghka 72 347 0 03 Jul 2015
Programming with models: writing statistical algorithms for general model structures with NIMBLE P. de Valpine Daniel Turek C. Paciorek Clifford Anderson-Bergman D. Lang Rastislav Bodík 88 857 0 19 May 2015
On Markov chain Monte Carlo methods for tall data Rémi Bardenet Arnaud Doucet Chris Holmes 73 279 0 11 May 2015
Sequential Monte Carlo Methods for System Identification Thomas B. Schon Fredrik Lindsten J. Dahlin Johan Waagberg C. A. Naesseth Andreas Svensson L. Dai 92 79 0 20 Mar 2015
Biips: Software for Bayesian Inference with Interacting Particle Systems A. Todeschini François Caron Marc Fuentes P. Legrand P. Del Moral 58 26 0 11 Dec 2014
Divide-and-Conquer with Sequential Monte Carlo Fredrik Lindsten A. M. Johansen C. A. Naesseth Bonnie Kirkpatrick Thomas B. Schon J. Aston Alexandre Bouchard-Côté 93 45 0 19 Jun 2014
Sequential Monte Carlo with Highly Informative Observations P. Del Moral Lawrence M. Murray 93 53 0 16 May 2014
Venture: a higher-order probabilistic programming platform with programmable inference Vikash K. Mansinghka Daniel Selsam Yura N. Perov 87 256 0 01 Apr 2014
A Compilation Target for Probabilistic Programming Languages Brooks Paige Frank Wood 97 80 0 03 Mar 2014
Sequential Quasi-Monte Carlo Mathieu Gerber Nicolas Chopin 152 56 0 17 Feb 2014
Bayesian State-Space Modelling on High-Performance Hardware Using LibBi Lawrence M. Murray 97 113 0 14 Jun 2013
Twisted particle filters N. Whiteley Anthony Lee 126 41 0 30 Sep 2012
Church: a language for generative models Noah D. Goodman Vikash K. Mansinghka Daniel M. Roy Keith Bonawitz J. Tenenbaum 110 820 0 13 Jun 2012
On Disturbance State-Space Models and the Particle Marginal Metropolis-Hastings Sampler Lawrence M. Murray E. Jones J. Parslow 112 31 0 28 Feb 2012
SMC^2: an efficient algorithm for sequential analysis of state-space models Nicolas Chopin Pierre E. Jacob O. Papaspiliopoulos 103 357 0 07 Jan 2011