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2006.08655
Cited By
Variational Bayesian Monte Carlo with Noisy Likelihoods
15 June 2020
Luigi Acerbi
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Papers citing
"Variational Bayesian Monte Carlo with Noisy Likelihoods"
31 / 31 papers shown
Title
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Unbiased and Efficient Log-Likelihood Estimation with Inverse Binomial Sampling
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Luigi Acerbi
W. Ma
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Energy and Policy Considerations for Deep Learning in NLP
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Ananya Ganesh
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Convergence Guarantees for Adaptive Bayesian Quadrature Methods
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Philipp Hennig
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Automatic Posterior Transformation for Likelihood-Free Inference
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M. Nonnenmacher
Jakob H. Macke
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Parallel Gaussian process surrogate Bayesian inference with noisy likelihood evaluations
Marko Jarvenpaa
Michael U. Gutmann
Aki Vehtari
Pekka Marttinen
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03 May 2019
Active Multi-Information Source Bayesian Quadrature
A. Gessner
Javier I. González
Maren Mahsereci
31
30
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27 Mar 2019
Automated Model Selection with Bayesian Quadrature
Henry Chai
Jean-François Ton
Roman Garnett
Michael A. Osborne
25
11
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26 Feb 2019
Variational Bayesian Monte Carlo
Luigi Acerbi
BDL
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64
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12 Oct 2018
Evaluating Gaussian Process Metamodels and Sequential Designs for Noisy Level Set Estimation
Xiong Lyu
M. Binois
M. Ludkovski
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24
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18 Jul 2018
Why Is My Classifier Discriminatory?
Irene Y. Chen
Fredrik D. Johansson
David Sontag
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42
395
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30 May 2018
Yes, but Did It Work?: Evaluating Variational Inference
Yuling Yao
Aki Vehtari
Daniel P. Simpson
Andrew Gelman
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136
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07 Feb 2018
Flexible statistical inference for mechanistic models of neural dynamics
Jan-Matthis Lueckmann
P. J. Gonçalves
Giacomo Bassetto
Kaan Öcal
M. Nonnenmacher
Jakob H. Macke
78
241
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06 Nov 2017
Constrained Bayesian Optimization with Noisy Experiments
Benjamin Letham
Brian Karrer
Guilherme Ottoni
E. Bakshy
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298
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21 Jun 2017
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search
Luigi Acerbi
Wei Ji
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218
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11 May 2017
Efficient acquisition rules for model-based approximate Bayesian computation
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Michael U. Gutmann
Arijus Pleska
Aki Vehtari
Pekka Marttinen
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03 Apr 2017
Adaptive Gaussian process approximation for Bayesian inference with expensive likelihood functions
Hongqiao Wang
Jinglai Li
GP
33
61
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29 Mar 2017
Variational Boosting: Iteratively Refining Posterior Approximations
Andrew C. Miller
N. Foti
Ryan P. Adams
38
124
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20 Nov 2016
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria
Marko Jarvenpaa
Michael U. Gutmann
Aki Vehtari
Pekka Marttinen
86
41
0
20 Oct 2016
Fast
ε
ε
ε
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George Papamakarios
Iain Murray
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76
158
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20 May 2016
Variational Inference: A Review for Statisticians
David M. Blei
A. Kucukelbir
Jon D. McAuliffe
BDL
147
4,748
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04 Jan 2016
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees
François‐Xavier Briol
Chris J. Oates
Mark Girolami
Michael A. Osborne
48
89
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08 Jun 2015
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models
Michael U. Gutmann
J. Corander
78
285
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14 Jan 2015
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
421
149,474
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22 Dec 2014
Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature
Tom Gunter
Michael A. Osborne
Roman Garnett
Philipp Hennig
Stephen J. Roberts
TPM
29
104
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03 Nov 2014
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
315
16,972
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20 Dec 2013
Practical Bayesian Optimization of Machine Learning Algorithms
Jasper Snoek
Hugo Larochelle
Ryan P. Adams
240
7,883
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13 Jun 2012
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning
E. Brochu
Vlad M. Cora
Nando de Freitas
GP
91
2,437
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12 Dec 2010
Cases for the nugget in modeling computer experiments
R. Gramacy
Herbert K. H. Lee
98
279
0
26 Jul 2010
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