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C3: Lightweight Incrementalized MCMC for Probabilistic Programs using
  Continuations and Callsite Caching
v1v2 (latest)

C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching

7 September 2015
Daniel E. Ritchie
Andreas Stuhlmuller
Noah D. Goodman
ArXiv (abs)PDFHTML

Papers citing "C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching"

9 / 9 papers shown
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
385
13
0
22 Aug 2022
Tensor Program Optimization with Probabilistic Programs
Tensor Program Optimization with Probabilistic ProgramsNeural Information Processing Systems (NeurIPS), 2022
Junru Shao
Xiyou Zhou
Siyuan Feng
Bohan Hou
Ruihang Lai
Hongyi Jin
Wuwei Lin
Masahiro Masuda
Cody Hao Yu
Tianqi Chen
369
60
0
26 May 2022
Nonparametric Hamiltonian Monte Carlo
Nonparametric Hamiltonian Monte CarloInternational Conference on Machine Learning (ICML), 2021
Carol Mak
Fabian Zaiser
C.-H. Luke Ong
222
7
0
18 Jun 2021
Accelerating Metropolis-Hastings with Lightweight Inference Compilation
Accelerating Metropolis-Hastings with Lightweight Inference Compilation
Feynman T. Liang
Nimar S. Arora
N. Tehrani
Y. Li
Michael Tingley
E. Meijer
221
0
0
23 Oct 2020
PClean: Bayesian Data Cleaning at Scale with Domain-Specific
  Probabilistic Programming
PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic ProgrammingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Alexander K. Lew
Monica Agrawal
David Sontag
Vikash K. Mansinghka
607
36
0
23 Jul 2020
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 SupportInternational Conference on Machine Learning (ICML), 2019
Yuanshuo Zhou
Hongseok Yang
Yee Whye Teh
Tom Rainforth
TPM
375
20
0
29 Oct 2019
An Introduction to Probabilistic Programming
An Introduction to Probabilistic Programming
Jan-Willem van de Meent
Brooks Paige
Hongseok Yang
Frank Wood
GP
379
220
0
27 Sep 2018
Inference Compilation and Universal Probabilistic Programming
Inference Compilation and Universal Probabilistic Programming
T. Le
A. G. Baydin
Frank Wood
UQCV
555
147
0
31 Oct 2016
Swift: Compiled Inference for Probabilistic Programming Languages
Swift: Compiled Inference for Probabilistic Programming LanguagesInternational Joint Conference on Artificial Intelligence (IJCAI), 2016
Yi Wu
Lei Li
Stuart J. Russell
Rastislav Bodík
198
30
0
30 Jun 2016
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