110 citations · 461 across the 50 of their papers we have counts for
6 papers · 1 filter
Regularized Zero-Variance Control Variates
Leah F. South, Chris J. Oates, Antonietta Mira +1
Zero-variance control variates (ZV-CV) are a post-processing method to reduce the variance of Monte Carlo estimators of expectations using the derivatives of the log target. Once t…
Robust Bayesian Synthetic Likelihood via a Semi-Parametric Approach
Ziwen An, David J. Nott, Christopher Drovandi
Bayesian synthetic likelihood (BSL) is now a well established method for performing approximate Bayesian parameter estimation for simulation-based models that do not possess a trac…
Optimal Bayesian design for model discrimination via classification
Markus Hainy, David J. Price, Olivier Restif +1
Performing optimal Bayesian design for discriminating between competing models is computationally intensive as it involves estimating posterior model probabilities for thousands of…
Unbiased and Consistent Nested Sampling via Sequential Monte Carlo
Robert Salomone, Leah F. South, Christopher Drovandi +2
We introduce a new class of sequential Monte Carlo methods which reformulates the essence of the nested sampling method of Skilling (2006) in terms of sequential Monte Carlo techni…
Approximating the Likelihood in Approximate Bayesian Computation
Christopher C Drovandi, Clara Grazian, Kerrie Mengersen +1
This chapter will appear in the forthcoming Handbook of Approximate Bayesian Computation (2018). The conceptual and methodological framework that underpins approximate Bayesian com…
ABC and Indirect Inference
Christopher C Drovandi
This chapter will appear in the forthcoming Handbook of Approximate Bayesian Computation (2018). Indirect inference (II) is a classical likelihood-free approach that pre-dates the…