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1906.03028
Cited By
Automatic Reparameterisation of Probabilistic Programs
7 June 2019
Maria I. Gorinova
Dave Moore
Matthew D. Hoffman
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Papers citing
"Automatic Reparameterisation of Probabilistic Programs"
10 / 10 papers shown
Title
Efficiently Vectorized MCMC on Modern Accelerators
Hugh Dance
Pierre Glaser
Peter Orbanz
Ryan P. Adams
85
0
0
20 Mar 2025
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models
Jinlin Lai
Justin Domke
Daniel Sheldon
128
0
0
31 Oct 2024
SoftCVI: Contrastive variational inference with self-generated soft labels
Daniel Ward
Mark Beaumont
Matteo Fasiolo
BDL
233
1
0
22 Jul 2024
Supporting Bayesian modelling workflows with iterative filtering for multiverse analysis
Anna Elisabeth Riha
Nikolas Siccha
Antti Oulasvirta
Aki Vehtari
69
0
0
02 Apr 2024
Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference
Philipp Reiser
Javier Enrique Aguilar
A. Guthke
Paul-Christian Bürkner
151
3
0
08 Dec 2023
Automatically Marginalized MCMC in Probabilistic Programming
Jinlin Lai
Javier Burroni
Hui Guan
Daniel Sheldon
87
3
0
01 Feb 2023
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference
Wonyeol Lee
Xavier Rival
Hongseok Yang
98
10
0
22 Aug 2022
Guaranteed Bounds for Posterior Inference in Universal Probabilistic Programming
Raven Beutner
Luke Ong
Fabian Zaiser
62
12
0
06 Apr 2022
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling
Gianluigi Silvestri
Emily Fertig
David A. Moore
L. Ambrogioni
BDL
TPM
AI4CE
99
4
0
12 Oct 2021
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors
Yuling Yao
Aki Vehtari
Andrew Gelman
92
63
0
22 Jun 2020
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