Variational Bayesian Monte Carlo with Noisy Likelihoods

15 June 2020

Papers citing "Variational Bayesian Monte Carlo with Noisy Likelihoods"

31 / 31 papers shown

Title
Bayesian Adaptive Calibration and Optimal Design Rafael Oliveira Dino Sejdinovic David Howard Edwin Bonilla 140 0 0 20 Jan 2025
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC F. Llorente Luca Martino Jesse Read D. Delgado OffRL 123 13 0 03 Jan 2025
Bayesian Synthetic Likelihood David T. Frazier Christopher C. Drovandi David J. Nott 107 217 0 09 May 2023
Unbiased and Efficient Log-Likelihood Estimation with Inverse Binomial Sampling B. V. Opheusden Luigi Acerbi W. Ma 42 37 0 12 Jan 2020
Energy and Policy Considerations for Deep Learning in NLP Emma Strubell Ananya Ganesh Andrew McCallum 53 2,633 0 05 Jun 2019
Convergence Guarantees for Adaptive Bayesian Quadrature Methods Motonobu Kanagawa Philipp Hennig 42 35 0 24 May 2019
Automatic Posterior Transformation for Likelihood-Free Inference David S. Greenberg M. Nonnenmacher Jakob H. Macke 176 322 0 17 May 2019
Parallel Gaussian process surrogate Bayesian inference with noisy likelihood evaluations Marko Jarvenpaa Michael U. Gutmann Aki Vehtari Pekka Marttinen 39 40 0 03 May 2019
Active Multi-Information Source Bayesian Quadrature A. Gessner Javier I. González Maren Mahsereci 43 30 0 27 Mar 2019
Automated Model Selection with Bayesian Quadrature Henry Chai Jean-François Ton Roman Garnett Michael A. Osborne 30 11 0 26 Feb 2019
Variational Bayesian Monte Carlo Luigi Acerbi BDL 39 64 0 12 Oct 2018
Evaluating Gaussian Process Metamodels and Sequential Designs for Noisy Level Set Estimation Xiong Lyu M. Binois M. Ludkovski 17 24 0 18 Jul 2018
Why Is My Classifier Discriminatory? Irene Y. Chen Fredrik D. Johansson David Sontag FaML 54 395 0 30 May 2018
Yes, but Did It Work?: Evaluating Variational Inference Yuling Yao Aki Vehtari Daniel P. Simpson Andrew Gelman 39 136 0 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 110 241 0 06 Nov 2017
Constrained Bayesian Optimization with Noisy Experiments Benjamin Letham Brian Karrer Guilherme Ottoni E. Bakshy 40 299 0 21 Jun 2017
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search Luigi Acerbi Wei Ji 41 219 0 11 May 2017
Efficient acquisition rules for model-based approximate Bayesian computation Marko Jarvenpaa Michael U. Gutmann Arijus Pleska Aki Vehtari Pekka Marttinen TPM 93 69 0 03 Apr 2017
Adaptive Gaussian process approximation for Bayesian inference with expensive likelihood functions Hongqiao Wang Jinglai Li GP 40 61 0 29 Mar 2017
Variational Boosting: Iteratively Refining Posterior Approximations Andrew C. Miller N. Foti Ryan P. Adams 43 125 0 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 113 41 0 20 Oct 2016
Fast $ε$ -free Inference of Simulation Models with Bayesian Conditional Density Estimation George Papamakarios Iain Murray TPM 104 158 0 20 May 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 181 4,748 0 04 Jan 2016
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees François‐Xavier Briol Chris J. Oates Mark Girolami Michael A. Osborne 53 89 0 08 Jun 2015
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models Michael U. Gutmann J. Corander 104 285 0 14 Jan 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 815 149,474 0 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 34 104 0 03 Nov 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 362 16,962 0 20 Dec 2013
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 290 7,883 0 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 116 2,437 0 12 Dec 2010
Cases for the nugget in modeling computer experiments R. Gramacy Herbert K. H. Lee 114 279 0 26 Jul 2010