Bayes Reading Group: Rafael Cabral (King Abdullah University of Science and Technology)

Friday Dec 16, 2022, 11:00 AM → 12:00 PM America/New_York

3rd Floor Conference Room/3-Flatiron Institute (162 5th Avenue)

Discussion Lead: Rafael Cabral

Topic: Correcting the Laplace Method with Variational Bayes

Abstract: Approximate inference methods like the Laplace method, Laplace approximations, and variational methods, amongst others, are popular methods when exact inference is not feasible due to the complexity of the model or the abundance of data. This week's paper proposes a hybrid approximate method, namely Low-Rank Variational Bayes correction (VBC), that uses the Laplace method and, subsequently, a Variational Bayes correction to the posterior mean. The cost is essentially that of the Laplace method, which ensures the scalability of the method. The method and its advantages are illustrated with simulated and real data on a small and large scale.

Reference: https://arxiv.org/abs/2111.12945