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Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients

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A Bayesian Perspective on Training Speed and Model Selection

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Bayesian Image Classification with Deep Convolutional Gaussian Processes

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Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty

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Variational Gaussian Process Models without Matrix Inverses

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Bayesian Layers: A Module for Neural Network Uncertainty

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Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models

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Rates of Convergence for Sparse Variational Gaussian Process Regression

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Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes

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Learning Invariances using the Marginal Likelihood

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