63 citations · 203 across the 11 of their papers we have counts for
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stat.ML2021★ 11 cited
Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning
Alexander Immer, Matthias Bauer, Vincent Fortuin +2
Marginal-likelihood based model-selection, even though promising, is rarely used in deep learning due to estimation difficulties. Instead, most approaches rely on validation data,…
stat.ML2021★ 1 cited
Generalized Doubly Reparameterized Gradient Estimators
Matthias Bauer, Andriy Mnih
Efficient low-variance gradient estimation enabled by the reparameterization trick (RT) has been essential to the success of variational autoencoders. Doubly-reparameterized gradie…