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A New Approach to Probabilistic Programming Inference

3 July 2015

Frank Wood

Jan-Willem van de Meent

Vikash K. Mansinghka

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Papers citing "A New Approach to Probabilistic Programming Inference"

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Title
Elements of Sequential Monte Carlo C. A. Naesseth Fredrik Lindsten Thomas B. Schon 75 97 0 12 Mar 2019
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models Yuanshuo Zhou Bradley Gram-Hansen Tobias Kohn Tom Rainforth Hongseok Yang Frank Wood 80 25 0 06 Mar 2019
ProBO: Versatile Bayesian Optimization Using Any Probabilistic Programming Language Willie Neiswanger Kirthevasan Kandasamy Barnabás Póczós J. Schneider Eric Xing 94 18 0 31 Jan 2019
Soft Constraints for Inference with Declarative Knowledge Zenna Tavares Javier Burroni Edgar Minaysan Armando Solar-Lezama Rajesh Ranganath 43 2 0 16 Jan 2019
A Generalization of Hierarchical Exchangeability on Trees to Directed Acyclic Graphs Paul Jung Jiho Lee S. Staton Hongseok Yang 47 9 0 15 Dec 2018
Doubly Bayesian Optimization Alexander Lavin 38 0 0 11 Dec 2018
Nested Reasoning About Autonomous Agents Using Probabilistic Programs I. Seaman Jan-Willem van de Meent David Wingate LRM 83 13 0 04 Dec 2018
Probabilistic Programming with Densities in SlicStan: Efficient, Flexible and Deterministic Maria I. Gorinova Andrew D. Gordon Charles Sutton 77 24 0 02 Nov 2018
Automated learning with a probabilistic programming language: Birch Lawrence M. Murray Thomas B. Schon 76 63 0 02 Oct 2018
Inference Over Programs That Make Predictions Yura N. Perov 35 2 0 02 Oct 2018
An Introduction to Probabilistic Programming Jan-Willem van de Meent Brooks Paige Hongseok Yang Frank Wood GP 88 200 0 27 Sep 2018
Scenic: A Language for Scenario Specification and Scene Generation Daniel J. Fremont T. Dreossi Shromona Ghosh Xiangyu Yue Alberto L. Sangiovanni-Vincentelli Sanjit A. Seshia 76 263 0 25 Sep 2018
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model A. G. Baydin Lukas Heinrich W. Bhimji Lei Shao Saeid Naderiparizi ... Philip Torr Victor W. Lee P. Prabhat Kyle Cranmer Frank Wood 90 31 0 20 Jul 2018
Tensor Monte Carlo: particle methods for the GPU era Laurence Aitchison BDL DRL 85 13 0 22 Jun 2018
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms Yi Wu Siddharth Srivastava N. Hay S. Du Stuart J. Russell 68 25 0 06 Jun 2018
Reparameterization Gradient for Non-differentiable Models Wonyeol Lee Hangyeol Yu Hongseok Yang DRL 125 32 0 01 Jun 2018
Mining gold from implicit models to improve likelihood-free inference Johann Brehmer Gilles Louppe J. Pavez Kyle Cranmer AI4CE TPM 188 181 0 30 May 2018
Hamiltonian Monte Carlo for Probabilistic Programs with Discontinuities Bradley Gram-Hansen Yuanshuo Zhou Tobias Kohn Tom Rainforth Hongseok Yang Frank Wood 26 3 0 07 Apr 2018
Nesting Probabilistic Programs Tom Rainforth TPM 68 24 0 16 Mar 2018
Probabilistic supervised learning Frithjof Gressmann Franz J. Király Bilal A. Mateen Harald Oberhauser 50 15 0 02 Jan 2018
SERKET: An Architecture for Connecting Stochastic Models to Realize a Large-Scale Cognitive Model Tomoaki Nakamura Takayuki Nagai T. Taniguchi 3DV 64 44 0 04 Dec 2017
On Nesting Monte Carlo Estimators Tom Rainforth R. Cornish Hongseok Yang Andrew Warrington Frank Wood 154 132 0 18 Sep 2017
Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs Lawrence M. Murray Daniel Lundén J. Kudlicka David Broman Thomas B. Schon 64 60 0 25 Aug 2017
Bayesian Optimization for Probabilistic Programs Tom Rainforth T. Le Jan-Willem van de Meent Michael A. Osborne Frank Wood TPM 72 27 0 13 Jul 2017
Learning Disentangled Representations with Semi-Supervised Deep Generative Models Siddharth Narayanaswamy Brooks Paige Jan-Willem van de Meent Alban Desmaison Noah D. Goodman Pushmeet Kohli Frank Wood Philip Torr DRL CoGe 185 363 0 01 Jun 2017
Auto-Encoding Sequential Monte Carlo T. Le Maximilian Igl Tom Rainforth Tom Jin Frank Wood BDL DRL 345 153 0 29 May 2017
Probabilistic Program Abstractions Steven Holtzen T. Millstein Guy Van den Broeck 42 15 0 28 May 2017
Using Synthetic Data to Train Neural Networks is Model-Based Reasoning T. Le A. G. Baydin R. Zinkov Frank Wood SyDa OOD 160 89 0 02 Mar 2017
Bayesian Probabilistic Numerical Methods Jon Cockayne Chris J. Oates T. Sullivan Mark Girolami 106 166 0 13 Feb 2017
Deep Probabilistic Programming Dustin Tran Matthew D. Hoffman Rif A. Saurous E. Brevdo Kevin Patrick Murphy David M. Blei BDL 142 193 0 13 Jan 2017
A Convenient Category for Higher-Order Probability Theory C. Heunen Ohad Kammar S. Staton Hongseok Yang 101 161 0 10 Jan 2017
Encapsulating models and approximate inference programs in probabilistic modules Marco F. Cusumano-Towner Vikash K. Mansinghka TPM 19 2 0 14 Dec 2016
On the Pitfalls of Nested Monte Carlo Tom Rainforth R. Cornish Hongseok Yang Frank Wood 64 9 0 03 Dec 2016
Tuning the Scheduling of Distributed Stochastic Gradient Descent with Bayesian Optimization Valentin Dalibard Michael Schaarschmidt Eiko Yoneki 29 2 0 01 Dec 2016
Probabilistic structure discovery in time series data David Janz Brooks Paige Tom Rainforth Jan-Willem van de Meent Frank Wood AI4TS 20 9 0 21 Nov 2016
Inference Compilation and Universal Probabilistic Programming T. Le A. G. Baydin Frank Wood UQCV 219 143 0 31 Oct 2016
Edward: A library for probabilistic modeling, inference, and criticism Dustin Tran A. Kucukelbir Adji Bousso Dieng Maja R. Rudolph Dawen Liang David M. Blei 113 300 0 31 Oct 2016
Deep Amortized Inference for Probabilistic Programs Daniel E. Ritchie Paul Horsfall Noah D. Goodman TPM 111 82 0 18 Oct 2016
Probabilistic Safety Programs Ashish Kapoor Debadeepta Dey S. Shah 25 0 0 17 Oct 2016
Logical Induction Scott Garrabrant Tsvi Benson-Tilsen Andrew Critch N. Soares Jessica Taylor 84 39 0 12 Sep 2016
Generic Inference in Latent Gaussian Process Models Edwin V. Bonilla K. Krauth Amir Dezfouli BDL 66 28 0 02 Sep 2016
Swift: Compiled Inference for Probabilistic Programming Languages Yi Wu Lei Li Stuart J. Russell Rastislav Bodík 96 29 0 30 Jun 2016
Spreadsheet Probabilistic Programming Mike Wu Yura N. Perov Frank Wood Hongseok Yang 49 3 0 14 Jun 2016
Post-Inference Prior Swapping Willie Neiswanger Eric Xing 19 1 0 02 Jun 2016
Applications of Probabilistic Programming (Master's thesis, 2015) Yura N. Perov 55 4 0 31 May 2016
Composing inference algorithms as program transformations R. Zinkov Chung-chieh Shan TPM 83 30 0 06 Mar 2016
Automatic Differentiation Variational Inference A. Kucukelbir Dustin Tran Rajesh Ranganath Andrew Gelman David M. Blei 133 719 0 02 Mar 2016
Inference Networks for Sequential Monte Carlo in Graphical Models Brooks Paige Frank Wood BDL 165 110 0 22 Feb 2016
Interacting Particle Markov Chain Monte Carlo Tom Rainforth C. A. Naesseth Fredrik Lindsten Brooks Paige Jan-Willem van de Meent Arnaud Doucet Frank Wood 72 34 0 16 Feb 2016
$Bayesian inference in non-Markovian state-space models with applications to fractional order systems$ Bayesian inference in non-Markovian state-space models with applications to fractional order systems Pierre E. Jacob S. Alavi A. Mahdi S. Payne David A. Howey 53 22 0 28 Jan 2016