50 citations · 91 across the 5 of their papers we have counts for
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stat.ML2023
Fast post-process Bayesian inference with Variational Sparse Bayesian Quadrature
Chengkun Li, Grégoire Clarté, Martin Jørgensen +1
In applied Bayesian inference scenarios, users may have access to a large number of pre-existing model evaluations, for example from maximum-a-posteriori (MAP) optimization runs. H…
stat.ML2020★ 29 cited
Variational Bayesian Monte Carlo with Noisy Likelihoods
Luigi Acerbi
Variational Bayesian Monte Carlo (VBMC) is a recently introduced framework that uses Gaussian process surrogates to perform approximate Bayesian inference in models with black-box,…
stat.ML2018★ 10 cited
Variational Bayesian Monte Carlo
Luigi Acerbi
Many probabilistic models of interest in scientific computing and machine learning have expensive, black-box likelihoods that prevent the application of standard techniques for Bay…