Seminar: Convolutional Gaussian processes

SpeakerMark van der Wilk
AffiliationUniversity of Cambridge
DateFriday, 17 Nov 2017
Time13:00 - 14:00
LocationRoberts Building G08 Sir David Davies LT
Event seriesDeepMind CSML Seminar Series

Gaussian processes are models that are equivalent to neural networks with infinitely many hidden units, and have many desirable properties, such as tractable Bayesian inference and sensible estimates. In recent years, there has been much progress on approximate inference for large datasets and non-conjugate likelihoods. However, the model structure of Gaussian processes has remained simple, especially compared to deep models. In this talk, we show how convolutional structure can be embedded in a Gaussian process and how to construct an tailored variational inference scheme for practical and accurate inference. We show that this structure significantly improves performance on classification tasks, as was seen in neural networks. We hope that this work will inspire work on more interesting Gaussian process models, where we obtain the benefits of both accurate inference and complex model structure.

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