Robert Boschgmbh

Marcello Carioni

Max Welling

Tim Genewein

Patrick Forré

Giorgio Patrini

A lossy data compressor for physical measurement data, comprising a parametrized mapping network hat, when applied to a measurement data point x in a space X, produces a point z in a lower-dimensional manifold Z, and configured to provide a point z on manifold Z as output in response to receiving a data point x as input, wherein the manifold Z is a continuous hypersurface that only admits fully continuous paths between any two points on the hypersurface; and the parameters &#x3b8; of the mapping network are trainable or trained towards an objective that comprises minimizing, on the manifold Z, a distance between a given prior distribution Pand a distribution Pinduced on manifold Z by mapping a given set Pof physical measurement data from X onto Z using the mapping network, according to a given distance measure.

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Graz, Austria

Marcello Carioni