667 citations · 1.5k across the 26 of their papers we have counts for
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stat.ML2014
Manifold Gaussian Processes for Regression
Roberto Calandra, Jan Peters, Carl Edward Rasmussen +1
Off-the-shelf Gaussian Process (GP) covariance functions encode smoothness assumptions on the structure of the function to be modeled. To model complex and non-differentiable funct…
stat.ML2014★ 70 cited
Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models
Yarin Gal, Mark van der Wilk, Carl E. Rasmussen
Gaussian processes (GPs) are a powerful tool for probabilistic inference over functions. They have been applied to both regression and non-linear dimensionality reduction, and offe…