Interpolation in generative models

Struski, Łukasz, Tabor, Jacek, Podolak, Igor, Nowak, Aleksandra

arXiv.org Machine Learning 

We show how to construct smooth and realistic interpolations for generative models, with arbitrary, not necessarily Gaussian, prior. The crucial idea is based on the construction on the realisticity index of a curve, which maximisation, as we show, leads to a search of a geodesic with respect to the corresponding Riemann structure.

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