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Veit David Wild

2 accepted papers

2023

A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods

NeurIPS 2023oral

We establish the first mathematically rigorous link between Bayesian, variational Bayesian, and ensemble methods. A key step towards this it to reformulate the non-convex optimisation problem typically encountered in deep learning as a convex optimisation in the space of probability measures. On a t…

Cited by 15SourcePDFScholar
2022

Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning

NeurIPS 2022accept

We develop a framework for generalized variational inference in infinite-dimensional function spaces and use it to construct a method termed Gaussian Wasserstein inference (GWI). GWI leverages the Wasserstein distance between Gaussian measures on the Hilbert space of square-integrable functions in o…