A variational inference-based framework for multi-output Gaussian process latent variable models on tails-up spatio-temporal stream networks using stream distance and process convolution.
Distribution properties of a measurement series of river water temperature at different time resolution levels (based on the example of the Lowland River Note
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The Bayesian Gaussian Process Latent Variable Model for Spatio-Temporal Stream Networks
A variational inference-based framework for multi-output Gaussian process latent variable models on tails-up spatio-temporal stream networks using stream distance and process convolution.