The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 19, 2021

Filed:

May. 23, 2019
Applicant:

Robert Bosch Gmbh, Stuttgart, DE;

Inventors:

Marcello Carioni, Graz, AT;

Giorgio Patrini, Amsterdam, NL;

Max Welling, Bussum, NL;

Patrick Forré, Amsterdam, NL;

Tim Genewein, London, GB;

Assignee:

Robert Bosch GmbH, Stuttgart, DE;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G05D 1/00 (2006.01); G06N 20/00 (2019.01); B60W 10/04 (2006.01); B60W 10/18 (2012.01); B60W 10/20 (2006.01); B60W 50/00 (2006.01); B60W 50/14 (2020.01);
U.S. Cl.
CPC ...
G05D 1/0088 (2013.01); B60W 10/04 (2013.01); B60W 10/18 (2013.01); B60W 10/20 (2013.01); B60W 50/0098 (2013.01); B60W 50/14 (2013.01); G05D 1/0061 (2013.01); G06N 20/00 (2019.01); B60W 2050/143 (2013.01);
Abstract

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 θ 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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