21 citations · 50 across the 6 of their papers we have counts for
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stat.ML2018
Orthogonally Decoupled Variational Gaussian Processes
Hugh Salimbeni, Ching-An Cheng, Byron Boots +1
Gaussian processes (GPs) provide a powerful non-parametric framework for reasoning over functions. Despite appealing theory, its superlinear computational and memory complexities h…
stat.ML2017★ 21 cited
Variational Inference for Gaussian Process Models with Linear Complexity
Ching-An Cheng, Byron Boots
Large-scale Gaussian process inference has long faced practical challenges due to time and space complexity that is superlinear in dataset size. While sparse variational Gaussian p…