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03/23/2022
On predictive inference for intractable models via approximate Bayesian computation
Approximate Bayesian computation (ABC) is commonly used for parameter es...
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04/08/2021
Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC
We present an efficient approach for doing approximate Bayesian inferenc...
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10/14/2019
Batch simulations and uncertainty quantification in Gaussian process surrogate-based approximate Bayesian computation
Surrogate models such as Gaussian processes (GP) have been proposed to a...
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10/14/2019
Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation
Surrogate models such as Gaussian processes (GP) have been proposed to a...
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05/03/2019
Parallel Gaussian process surrogate method to accelerate likelihood-free inference
We consider Bayesian inference when only a limited number of noisy log-l...
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11/27/2018
A Bayesian model of acquisition and clearance of bacterial colonization
Bacterial populations that colonize a host play important roles in host ...
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08/02/2017
ELFI: Engine for Likelihood Free Inference
The Engine for Likelihood-Free Inference (ELFI) is a Python software lib...
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04/03/2017
Efficient acquisition rules for model-based approximate Bayesian computation
Approximate Bayesian computation (ABC) is a method for Bayesian inferenc...
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10/20/2016