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Deep Amortized Inference for Probabilistic Programs

Deep Amortized Inference for Probabilistic Programs

18 October 2016
Daniel E. Ritchie
Paul Horsfall
Noah D. Goodman
    TPM
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Papers citing "Deep Amortized Inference for Probabilistic Programs"

15 / 15 papers shown
Title
Amortized Bayesian Multilevel Models
Amortized Bayesian Multilevel Models
Daniel Habermann
Marvin Schmitt
Lars Kühmichel
Andreas Bulling
Stefan T. Radev
Paul-Christian Bürkner
67
3
0
23 Aug 2024
Graphically Structured Diffusion Models
Graphically Structured Diffusion Models
Christian Weilbach
William Harvey
Frank D. Wood
DiffM
35
7
0
20 Oct 2022
Smoothness Analysis for Probabilistic Programs with Application to
  Optimised Variational Inference
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference
Wonyeol Lee
Xavier Rival
Hongseok Yang
18
9
0
22 Aug 2022
Variational Deep Image Restoration
Variational Deep Image Restoration
Jae Woong Soh
N. Cho
SupR
48
39
0
03 Jul 2022
Transformers Can Do Bayesian Inference
Transformers Can Do Bayesian Inference
Samuel G. Müller
Noah Hollmann
Sebastian Pineda Arango
Josif Grabocka
Frank Hutter
BDL
UQCV
22
140
0
20 Dec 2021
Nested Variational Inference
Nested Variational Inference
Heiko Zimmermann
Hao Wu
Babak Esmaeili
Jan-Willem van de Meent
BDL
24
20
0
21 Jun 2021
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic
  Programs with Stochastic Support
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support
Yuanshuo Zhou
Hongseok Yang
Yee Whye Teh
Tom Rainforth
TPM
29
19
0
29 Oct 2019
Monte Carlo Gradient Estimation in Machine Learning
Monte Carlo Gradient Estimation in Machine Learning
S. Mohamed
Mihaela Rosca
Michael Figurnov
A. Mnih
24
397
0
25 Jun 2019
Meta-learning of Sequential Strategies
Meta-learning of Sequential Strategies
Pedro A. Ortega
Jane X. Wang
Mark Rowland
Tim Genewein
Z. Kurth-Nelson
...
Yee Whye Teh
H. V. Hasselt
Nando de Freitas
M. Botvinick
Shane Legg
OffRL
22
96
0
08 May 2019
Likelihood-free MCMC with Amortized Approximate Ratio Estimators
Likelihood-free MCMC with Amortized Approximate Ratio Estimators
Joeri Hermans
Volodimir Begy
Gilles Louppe
29
20
0
10 Mar 2019
Relational inductive biases, deep learning, and graph networks
Relational inductive biases, deep learning, and graph networks
Peter W. Battaglia
Jessica B. Hamrick
V. Bapst
Alvaro Sanchez-Gonzalez
V. Zambaldi
...
Pushmeet Kohli
M. Botvinick
Oriol Vinyals
Yujia Li
Razvan Pascanu
AI4CE
NAI
94
3,078
0
04 Jun 2018
Learning 3D Shape Completion under Weak Supervision
Learning 3D Shape Completion under Weak Supervision
David Stutz
Andreas Geiger
3DPC
SSL
32
106
0
18 May 2018
Faithful Inversion of Generative Models for Effective Amortized
  Inference
Faithful Inversion of Generative Models for Effective Amortized Inference
Stefan Webb
Adam Goliñski
R. Zinkov
Siddharth Narayanaswamy
Tom Rainforth
Yee Whye Teh
Frank D. Wood
TPM
26
46
0
01 Dec 2017
Deep Probabilistic Programming
Deep Probabilistic Programming
Dustin Tran
Matthew D. Hoffman
Rif A. Saurous
E. Brevdo
Kevin Patrick Murphy
David M. Blei
BDL
33
193
0
13 Jan 2017
Automatic differentiation in machine learning: a survey
Automatic differentiation in machine learning: a survey
A. G. Baydin
Barak A. Pearlmutter
Alexey Radul
J. Siskind
PINN
AI4CE
ODL
32
2,746
0
20 Feb 2015
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