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cs.LG2024★ 2 cited
Scalable Multi-Output Gaussian Processes with Stochastic Variational Inference
Xiaoyu Jiang, Sokratia Georgaka, Magnus Rattray +1
The Multi-Output Gaussian Process is is a popular tool for modelling data from multiple sources. A typical choice to build a covariance function for a MOGP is the Linear Model of C…
cs.LG2024
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models
Xinxing Shi, Thomas Baldwin-McDonald, Mauricio A. Álvarez
Deep Gaussian Processes (DGPs) leverage a compositional structure to model non-stationary processes. DGPs typically rely on local inducing point approximations across intermediate…