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Michael R Andersen

2 accepted papers

2023

On the role of model uncertainties in Bayesian optimisation

UAI 2023poster

Bayesian Optimization (BO) is a popular method for black-box optimization, which relies on uncertainty as part of its decision-making process when deciding which experiment to perform next. However, not much work has addressed the effect of uncertainty on the performance of the BO algorithm and to w…

2020

Robust, Accurate Stochastic Optimization for Variational Inference

NeurIPS 2020poster

We examine the accuracy of black box variational posterior approximations for parametric models in a probabilistic programming context. The performance of these approximations depends on (1) how well the variational family approximates the true posterior distribution, (2) the choice of divergence, a…

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