Search Results for author: Astrid Dahl

Found 2 papers, 0 papers with code

Scalable Grouped Gaussian Processes via Direct Cholesky Functional Representations

no code implementations10 Mar 2019 Astrid Dahl, Edwin V. Bonilla

We consider multi-task regression models where observations are assumed to be a linear combination of several latent node and weight functions, all drawn from Gaussian process (GP) priors that allow nonzero covariance between grouped latent functions.

Gaussian Processes Variational Inference

Grouped Gaussian Processes for Solar Power Prediction

no code implementations7 Jun 2018 Astrid Dahl, Edwin V. Bonilla

We consider multi-task regression models where the observations are assumed to be a linear combination of several latent node functions and weight functions, which are both drawn from Gaussian process priors.

Gaussian Processes

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