A Gaussian Process Regression Model for Distribution Inputs

31 Jan 2017François BachocFabrice GamboaJean-Michel LoubesNil Venet

Monge-Kantorovich distances, otherwise known as Wasserstein distances, have received a growing attention in statistics and machine learning as a powerful discrepancy measure for probability distributions. In this paper, we focus on forecasting a Gaussian process indexed by probability distributions... (read more)

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