65 citations · 247 across the 13 of their papers we have counts for
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stat.ML2015★ 55 cited
MCMC for Variationally Sparse Gaussian Processes
James Hensman, Alexander G. de G. Matthews, Maurizio Filippone +1
Gaussian process (GP) models form a core part of probabilistic machine learning. Considerable research effort has been made into attacking three issues with GP models: how to compu…
stat.ML2015★ 6 cited
Spike and Slab Gaussian Process Latent Variable Models
Zhenwen Dai, James Hensman, Neil Lawrence
The Gaussian process latent variable model (GP-LVM) is a popular approach to non-linear probabilistic dimensionality reduction. One design choice for the model is the number of lat…