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Complex simulators have become a ubiquitous tool in many scientific disciplines, providing high-fidelity, implicit probabilistic models of natural and social phenomena.
Approximate Bayesian computation in population genetics
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Estimation of population growth or decline in genetically monitored populations
Mark A Beaumont · 2003
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Paul Marjoram, John Molitor, Vincent Plagnol, and Simon Tavaré · 2003
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Sequential monte carlo without likelihoods
Scott A Sisson, Yanan Fan, and Mark M Tanaka · 2007
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Particle filters for partially observed diffusions
Paul Fearnhead, Omiros Papaspiliopoulos, and Gareth O Roberts · 2008
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The pseudo-marginal approach for efficient Monte Carlo computations
Christophe Andrieu, Gareth O Roberts, et al · 2009
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Christophe Andrieu, Arnaud Doucet, and Roman Holenstein · 2010
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The safe Bayesian
Peter Grünwald · 2012
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On some properties of Markov chain Monte Carlo simulation methods based on the particle filter
Michael K Pitt, Ralph dos Santos Silva, Paolo Giordani, and Robert Kohn · 2012
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A Comparative Review of Dimension Reduction Methods in Approximate Bayesian Computation
M. G. B. Blum, M. A. Nunes, D. Prangle, and S. A. Sisson · 2013
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Bayesian model robustness via disparities
Giles Hooker and Anand N Vidyashankar · 2014
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Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator
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A general framework for updating belief distributions
Pier Giovanni Bissiri, Chris C Holmes, and Stephen G Walker · 2016
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A comparison of inferential methods for highly nonlinear state space models in ecology and epidemiology
Matteo Fasiolo, Natalya Pya, and Simon N Wood · 2016
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Robust Bayes estimation using the density power divergence
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K2-ABC: Approximate Bayesian Computation with Kernel Embeddings
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Probably approximate Bayesian computation: nonasymptotic convergence of ABC under misspecification
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Espen Bernton, Pierre E. Jacob, Mathieu Gerber, and Christian P. Robert · 2019
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A primer on PAC-Bayesian learning
Benjamin Guedj · 2019
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Generalized variational inference: Three arguments for deriving new posteriors
Jeremias Knoblauch, Jack Jewson, and Theodoros Damoulas · 2019
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ArviZ a unified library for exploratory analysis of Bayesian models in Python
Ravin Kumar, Colin Carroll, Ari Hartikainen, and Osvaldo A. Martin · 2019
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Bernoulli Race Particle Filters
Sebastian M. Schmon, Arnaud Doucet, and George Deligiannidis · 2019
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James Ridgway · 2017
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Principles of Bayesian inference using general divergence criteria
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Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β \beta -Divergences
Jeremias Knoblauch, Jack Jewson, and Theodoros Damoulas · 2018
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Approximate Bayesian computation
Mark A Beaumont · 2019
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Approximate Bayesian computation (ABC) gives exact results under the assumption of model error
Richard David Wilkinson · 2019
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Generalized Bayesian Filtering via Sequential Monte Carlo
Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, and Adam Johansen · 2020
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The frontier of simulation-based inference
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Model misspecification in approximate bayesian computation: consequences and diagnostics
Frazier, David T. and Robert, Christian P. and Rousseau, Judith · 2020
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Large-sample asymptotics of the pseudo-marginal method
S M Schmon, G Deligiannidis, A Doucet, and M K Pitt · 2020
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