Implicit posterior variational inference for deep Gaussian processes

Implicit posterior variational inference for deep Gaussian processes

A multi-layer deep Gaussian process (DGP) model is a hierarchical composition of GP models with a greater expressive power. Exact DGP inference is intractable, which has motivated the recent development of deterministic and stochastic approximation methods. Unfortunately, the deterministic approxima...

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Bibliographic Details
Main Author:	Jaillet, Patrick
Other Authors:	Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format:	Article
Language:	English
Published:	Morgan Kaufmann Publishers 2021
Online Access:	https://hdl.handle.net/1721.1/129355

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