SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data
Maud Lemercier 1 Cristopher Salvi 2 Thomas Cass 3 Edwin V. Bonilla 4 Theodoros Damoulas 1 Terry Lyons 2
Abstract vations N , with nave approaches having a time complexity
O(N 3 ). From a wide range of approximate techniques
Making predictions and quantifying their uncer- to scale inference in GP models to large datasets, “sparse”
tainty when the input data ...


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