1

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

Learning Invariances using the Marginal Likelihood

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

Convolutional Gaussian Processes

Understanding Probabilistic Sparse Gaussian Process Approximations

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