Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes

5 Aug 2020Panagiotis TsilifisPiyush PanditaSayan GhoshValeria AndreoliThomas VandeputteLiping Wang

We present a Bayesian approach to identify optimal transformations that map model input points to low dimensional latent variables. The "projection" mapping consists of an orthonormal matrix that is considered a priori unknown and needs to be inferred jointly with the GP parameters, conditioned on the available training data... (read more)

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