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1802.09411
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Principles of Bayesian Inference using General Divergence Criteria
26 February 2018
Jack Jewson
Jim Q. Smith
Chris Holmes
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Papers citing
"Principles of Bayesian Inference using General Divergence Criteria"
36 / 36 papers shown
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Differentially Private Statistical Inference through
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Sampling algorithms in statistical physics: a guide for statistics and machine learning
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Concentration of discrepancy-based approximate Bayesian computation via Rademacher complexity
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Daniele Durante
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Adaptation of the Tuning Parameter in General Bayesian Inference with Robust Divergence
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Robust Generalised Bayesian Inference for Intractable Likelihoods
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Foundations of Bayesian Learning from Synthetic Data
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Sebastian J. Vollmer
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Robust Bayesian Inference for Discrete Outcomes with the Total Variation Distance
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Lara Vomfell
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Finite mixture models do not reliably learn the number of components
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Robust Bayesian Classification Using an Optimistic Score Ratio
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Jose H. Blanchet
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Generalised Bayes Updates with
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Henri Pesonen
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Generalized Bayesian Filtering via Sequential Monte Carlo
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Ömer Deniz Akyildiz
Theodoros Damoulas
A. M. Johansen
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Frequentist Consistency of Generalized Variational Inference
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66
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On Robust Pseudo-Bayes Estimation for the Independent Non-homogeneous Set-up
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A. Basu
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MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy
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Robust Deep Gaussian Processes
Jeremias Knoblauch
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Generalized Variational Inference: Three arguments for deriving new Posteriors
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Jack Jewson
Theodoros Damoulas
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Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with
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81
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