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Normalizing Flows for Hierarchical Bayesian Analysis: A Gravitational
  Wave Population Study

Normalizing Flows for Hierarchical Bayesian Analysis: A Gravitational Wave Population Study

15 November 2022
David Ruhe
Kaze W. K. Wong
M. Cranmer
Patrick Forré
ArXivPDFHTML

Papers citing "Normalizing Flows for Hierarchical Bayesian Analysis: A Gravitational Wave Population Study"

5 / 5 papers shown
Title
Towards a robust and reliable deep learning approach for detection of
  compact binary mergers in gravitational wave data
Towards a robust and reliable deep learning approach for detection of compact binary mergers in gravitational wave data
S. Jadhav
Mihir Shrivastava
S. Mitra
OOD
11
9
0
20 Jun 2023
Comparative Study of Coupling and Autoregressive Flows through Robust
  Statistical Tests
Comparative Study of Coupling and Autoregressive Flows through Robust Statistical Tests
A. Coccaro
Marco Letizia
H. Reyes-González
Riccardo Torre
OOD
30
5
0
23 Feb 2023
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
270
5,660
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,136
0
06 Jun 2015
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,262
0
09 Jun 2012
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