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Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the
  Predictive Uncertainties

Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties

22 May 2020
J. Lindinger
David Reeb
C. Lippert
Barbara Rakitsch
    BDL
    UQCV
ArXivPDFHTML

Papers citing "Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties"

3 / 3 papers shown
Title
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models
Xinxing Shi
Thomas Baldwin-McDonald
Mauricio A. Álvarez
76
0
0
01 Jul 2024
Uncertainty Estimation for Multi-view Data: The Power of Seeing the
  Whole Picture
Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picture
M. Jung
He Zhao
Joanna Dipnall
Belinda Gabbe
Lan Du
UQCV
EDL
57
12
0
06 Oct 2022
Global inducing point variational posteriors for Bayesian neural
  networks and deep Gaussian processes
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes
Sebastian W. Ober
Laurence Aitchison
BDL
26
60
0
17 May 2020
1