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Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?

Many machine learning models require setting a parameter that controls their size before training, e.g. number of neurons in DNNs, or inducing points in GPs. Increasing capacity typically improves performance until all the information from the dataset is captured. After this point, computational cos…