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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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Concrete problems for autonomous vehicle safety: advantages of Bayesian deep learning

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Convolutional Gaussian Processes

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Understanding Probabilistic Sparse Gaussian Process Approximations

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Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models

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