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08/10/2023
Solving the Forecast Combination Puzzle
We demonstrate that the forecasting combination puzzle is a consequence ...
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05/15/2023
Bayesian inference for misspecified generative models
Bayesian inference is a powerful tool for combining information in compl...
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05/09/2023
Bayesian Synthetic Likelihood
Bayesian statistics is concerned with conducting posterior inference for...
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02/13/2023
Reliable Bayesian Inference in Misspecified Models
We provide a general solution to a fundamental open problem in Bayesian ...
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01/31/2023
Misspecification-robust Sequential Neural Likelihood
Simulation-based inference (SBI) techniques are now an essential tool fo...
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01/26/2023
Guaranteed Accuracy of Semi-Modular Posteriors
Bayesian inference has widely acknowledged advantages in many problems, ...
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12/07/2022
Bayesian Forecasting in the 21st Century: A Modern Review
The Bayesian statistical paradigm provides a principled and coherent app...
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12/05/2022
Better Together: pooling information in likelihood-free inference
Likelihood-free inference (LFI) methods, such as Approximate Bayesian co...
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10/23/2022
Testing model specification in approximate Bayesian computation
We present a procedure to diagnose model misspecification in situations ...
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08/01/2022
Computing Bayes: From Then 'Til Now'
This paper takes the reader on a journey through the history of Bayesian...
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07/14/2022
Improving the Accuracy of Marginal Approximations in Likelihood-Free Inference via Localisation
Likelihood-free methods are an essential tool for performing inference f...
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06/06/2022
The Impact of Sampling Variability on Estimated Combinations of Distributional Forecasts
We investigate the performance and sampling variability of estimated for...
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03/18/2022
Modularized Bayesian analyses and cutting feedback in likelihood-free inference
There has been much recent interest in modifying Bayesian inference for ...
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02/21/2022
Cutting feedback and modularized analyses in generalized Bayesian inference
Even in relatively simple settings, model misspecification can make the ...
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12/23/2021
ABC of the Future
Approximate Bayesian computation (ABC) has advanced in two decades from ...
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12/20/2021
Approximating Bayes in the 21st Century
The 21st century has seen an enormous growth in the development and use ...
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06/23/2021
A Note on the Accuracy of Variational Bayes in State Space Models: Inference and Prediction
Using theoretical and numerical results, we document the accuracy of com...
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04/29/2021
Loss-Based Variational Bayes Prediction
We propose a new method for Bayesian prediction that caters for models w...
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04/08/2021
Synthetic Likelihood in Misspecified Models: Consequences and Corrections
We analyse the behaviour of the synthetic likelihood (SL) method when th...
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03/03/2021
A Comparison of Likelihood-Free Methods With and Without Summary Statistics
Likelihood-free methods are useful for parameter estimation of complex m...
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09/21/2020
Optimal probabilistic forecasts: When do they work?
Proper scoring rules are used to assess the out-of-sample accuracy of pr...
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08/07/2020
Robust Approximate Bayesian Computation: An Adjustment Approach
We propose a novel approach to approximate Bayesian computation (ABC) th...
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06/25/2020
Robust and Efficient Approximate Bayesian Computation: A Minimum Distance Approach
In many instances, the application of approximate Bayesian methods is ha...
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06/18/2020
Approximate Maximum Likelihood for Complex Structural Models
Indirect Inference (I-I) is a popular technique for estimating complex p...
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04/14/2020
Computing Bayes: Bayesian Computation from 1763 to the 21st Century
The Bayesian statistical paradigm uses the language of probability to ex...
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12/29/2019
Focused Bayesian Prediction
We propose a new method for conducting Bayesian prediction that delivers...
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04/09/2019
Robust Approximate Bayesian Inference with Synthetic Likelihood
Bayesian synthetic likelihood (BSL) is now a well-established method for...
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12/20/2017
Approximate Bayesian Forecasting
Approximate Bayesian Computation (ABC) has become increasingly prominent...
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08/08/2017
