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BayesLDM: A Domain-Specific Language for Probabilistic Modeling of
  Longitudinal Data

BayesLDM: A Domain-Specific Language for Probabilistic Modeling of Longitudinal Data

12 September 2022
Ka-Yee Tung
Steven De La Torre
Mohamed El Mistiri
Rebecca Braga De Braganca
Eric B. Hekler
Misha Pavel
D. Rivera
Pedja Klasnja
D. Spruijt-Metz
Benjamin M. Marlin
ArXiv (abs)PDFHTML

Papers citing "BayesLDM: A Domain-Specific Language for Probabilistic Modeling of Longitudinal Data"

5 / 5 papers shown
Title
Composable Effects for Flexible and Accelerated Probabilistic
  Programming in NumPyro
Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro
Du Phan
Neeraj Pradhan
M. Jankowiak
66
360
0
24 Dec 2019
Simple, Distributed, and Accelerated Probabilistic Programming
Simple, Distributed, and Accelerated Probabilistic Programming
Like Hui
Matthew Hoffman
Siyuan Ma
Christopher Suter
Srinivas Vasudevan
Alexey Radul
M. Belkin
Rif A. Saurous
BDL
65
56
0
05 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
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
302
3,282
0
09 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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