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Summary Statistics in Approximate Bayesian Computation

Summary Statistics in Approximate Bayesian Computation

17 December 2015
D. Prangle
ArXiv (abs)PDFHTML

Papers citing "Summary Statistics in Approximate Bayesian Computation"

13 / 13 papers shown
Title
Nonparametric likelihood-free inference with Jensen-Shannon divergence
  for simulator-based models with categorical output
Nonparametric likelihood-free inference with Jensen-Shannon divergence for simulator-based models with categorical output
J. Corander
Ulpu Remes
Ida Holopainen
T. Koski
135
0
0
22 May 2022
Weakly informative priors and prior-data conflict checking for
  likelihood-free inference
Weakly informative priors and prior-data conflict checking for likelihood-free inference
Atlanta Chakraborty
David J. Nott
Michael Evans
47
4
0
21 Feb 2022
Approximate Bayesian Computation with Domain Expert in the Loop
Approximate Bayesian Computation with Domain Expert in the Loop
Ayush Bharti
Louis Filstroff
Samuel Kaski
TPM
120
9
0
28 Jan 2022
GRAFFL: Gradient-free Federated Learning of a Bayesian Generative Model
GRAFFL: Gradient-free Federated Learning of a Bayesian Generative Model
S. Hahn
Junghye Lee
FedML
15
2
0
29 Aug 2020
Convolutional Neural Networks as Summary Statistics for Approximate
  Bayesian Computation
Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation
Mattias Åkesson
Prashant Singh
Fredrik Wrede
Andreas Hellander
BDL
107
33
0
31 Jan 2020
Distance-learning For Approximate Bayesian Computation To Model a
  Volcanic Eruption
Distance-learning For Approximate Bayesian Computation To Model a Volcanic Eruption
Lorenzo Pacchiardi
Pierre Künzli
Marcel Schoengens
B. Chopard
Ritabrata Dutta
59
13
0
28 Sep 2019
Finding our Way in the Dark: Approximate MCMC for Approximate Bayesian
  Methods
Finding our Way in the Dark: Approximate MCMC for Approximate Bayesian Methods
Evgeny Levi
Radu V. Craiu
59
6
0
16 May 2019
Spectral Density-Based and Measure-Preserving ABC for partially observed
  diffusion processes. An illustration on Hamiltonian SDEs
Spectral Density-Based and Measure-Preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEs
E. Buckwar
M. Tamborrino
I. Tubikanec
78
36
0
04 Mar 2019
Partially Exchangeable Networks and Architectures for Learning Summary
  Statistics in Approximate Bayesian Computation
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation
Samuel Wiqvist
Pierre-Alexandre Mattei
Umberto Picchini
J. Frellsen
BDL
192
32
0
29 Jan 2019
Local dimension reduction of summary statistics for likelihood-free
  inference
Local dimension reduction of summary statistics for likelihood-free inference
Jukka Sirén
Samuel Kaski
57
2
0
25 Jan 2019
Machine Learning Accelerated Likelihood-Free Event Reconstruction in
  Dark Matter Direct Detection
Machine Learning Accelerated Likelihood-Free Event Reconstruction in Dark Matter Direct Detection
U. Simola
B. Pelssers
D. Barge
J. Conrad
J. Corander
122
11
0
23 Oct 2018
Bayesian inference for stochastic differential equation mixed effects
  models of a tumor xenography study
Bayesian inference for stochastic differential equation mixed effects models of a tumor xenography study
Umberto Picchini
J. Forman
51
24
0
09 Jul 2016
Asymptotically exact inference in differentiable generative models
Asymptotically exact inference in differentiable generative models
Matthew M. Graham
Amos J. Storkey
BDL
189
33
0
25 May 2016
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