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Compiling Stan to Generative Probabilistic Languages and Extension to
  Deep Probabilistic Programming
v1v2v3v4v5 (latest)

Compiling Stan to Generative Probabilistic Languages and Extension to Deep Probabilistic Programming

30 September 2018
Guillaume Baudart
Javier Burroni
Martin Hirzel
Louis Mandel
Avraham Shinnar
    BDL
ArXiv (abs)PDFHTML

Papers citing "Compiling Stan to Generative Probabilistic Languages and Extension to Deep Probabilistic Programming"

12 / 12 papers shown
Title
Probabilistic Programming with Densities in SlicStan: Efficient,
  Flexible and Deterministic
Probabilistic Programming with Densities in SlicStan: Efficient, Flexible and Deterministic
Maria I. Gorinova
Andrew D. Gordon
Charles Sutton
64
24
0
02 Nov 2018
Pyro: Deep Universal Probabilistic Programming
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
BDLGP
158
1,057
0
18 Oct 2018
Automated learning with a probabilistic programming language: Birch
Automated learning with a probabilistic programming language: Birch
Lawrence M. Murray
Thomas B. Schon
54
63
0
02 Oct 2018
An Introduction to Probabilistic Programming
An Introduction to Probabilistic Programming
Jan-Willem van de Meent
Brooks Paige
Hongseok Yang
Frank Wood
GP
80
200
0
27 Sep 2018
Learning Disentangled Representations with Semi-Supervised Deep
  Generative Models
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
DRLCoGe
166
363
0
01 Jun 2017
Deep Probabilistic Programming
Deep Probabilistic Programming
Dustin Tran
Matthew D. Hoffman
Rif A. Saurous
E. Brevdo
Kevin Patrick Murphy
David M. Blei
BDL
120
193
0
13 Jan 2017
Variational Inference: A Review for Statisticians
Variational Inference: A Review for Statisticians
David M. Blei
A. Kucukelbir
Jon D. McAuliffe
BDL
307
4,812
0
04 Jan 2016
Automatic Variational Inference in Stan
Automatic Variational Inference in Stan
A. Kucukelbir
Rajesh Ranganath
Andrew Gelman
David M. Blei
BDL
86
234
0
10 Jun 2015
Semi-Supervised Learning with Deep Generative Models
Semi-Supervised Learning with Deep Generative Models
Diederik P. Kingma
Danilo Jimenez Rezende
S. Mohamed
Max Welling
GANSSLBDL
105
2,742
0
20 Jun 2014
Venture: a higher-order probabilistic programming platform with
  programmable inference
Venture: a higher-order probabilistic programming platform with programmable inference
Vikash K. Mansinghka
Daniel Selsam
Yura N. Perov
84
256
0
01 Apr 2014
Church: a language for generative models
Church: a language for generative models
Noah D. Goodman
Vikash K. Mansinghka
Daniel M. Roy
Keith Bonawitz
J. Tenenbaum
110
819
0
13 Jun 2012
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian
  Monte Carlo
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
Matthew D. Hoffman
Andrew Gelman
189
4,315
0
18 Nov 2011
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