Towards a Kernel based Physical Interpretation of Model Uncertainty

30 Jan 2020Rishabh SinghJose C. Principe

This paper introduces a new information theoretic framework that provides a sensitive multi-modal quantification of time series uncertainty by leveraging a quantum physical description of the projected feature space in a Reproducing Kernel Hilbert Space (RKHS). We specifically modify the kernel mean embedding, which yields an intuitive physical interpretation of the signal structure, to produce a dynamic potential field, resulting in a new energy based formulation that exploits the mathematics of quantum theory... (read more)

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