36 citations · 138 across the 24 of their papers we have counts for
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stat.ML2018
Learning Causally-Generated Stationary Time Series
Wessel Bruinsma, Richard E. Turner
We present the Causal Gaussian Process Convolution Model (CGPCM), a doubly nonparametric model for causal, spectrally complex dynamical phenomena. The CGPCM is a generative model i…
stat.ML2018★ 15 cited
The Gaussian Process Autoregressive Regression Model (GPAR)
James Requeima, Will Tebbutt, Wessel Bruinsma +1
Multi-output regression models must exploit dependencies between outputs to maximise predictive performance. The application of Gaussian processes (GPs) to this setting typically y…