Patents by Inventor Sebastian Boblest

Sebastian Boblest has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11803732
    Abstract: A device and a computer-implemented method for classifying data, in particular for a Controller Area Network or an automotive Ethernet network. A plurality of messages is received from a communications network. A message that has a predefined message type is selected for an input variable for an input model of a plurality of input models of an artificial neural network associated with the predefined message type. The input variable is determined as a function of the message, and in an output area of the artificial neural network a prediction is output that is usable for classifying the message as a function of the input variable, or a reconstruction of an input variable is output that is usable for classifying the message as a function of this input variable.
    Type: Grant
    Filed: January 14, 2020
    Date of Patent: October 31, 2023
    Assignee: ROBERT BOSCH GMBH
    Inventors: Markus Hanselmann, Holger Ulmer, Katharina Dormann, Thilo Strauss, Andrej Junginger, Jens Stefan Buchner, Sebastian Boblest
  • Publication number: 20210264075
    Abstract: A method for creating a model of a technical system as a function of measured sensor data of the technical system. The method includes the following steps: initializing a symbolic regression problem. A list of mathematical functions is established, including at least one linear and/or non-linear function and/or at least a one-dimensional parameterizable characteristic curve. The at least one-dimensional characteristic curve is implemented by a Smoothed Grid Regression (SGR) model. Solving the symbolic regression problem with the aid of a genetic algorithm.
    Type: Application
    Filed: January 25, 2021
    Publication date: August 26, 2021
    Inventors: Andrej Junginger, Holger Ulmer, Jens Stefan Buchner, Patrick Engel, Sebastian Boblest
  • Publication number: 20200234101
    Abstract: A device and a computer-implemented method for classifying data, in particular for a Controller Area Network or an automotive Ethernet network. A plurality of messages is received from a communications network. A message that has a predefined message type is selected for an input variable for an input model of a plurality of input models of an artificial neural network associated with the predefined message type. The input variable is determined as a function of the message, and in an output area of the artificial neural network a prediction is output that is usable for classifying the message as a function of the input variable, or a reconstruction of an input variable is output that is usable for classifying the message as a function of this input variable.
    Type: Application
    Filed: January 14, 2020
    Publication date: July 23, 2020
    Inventors: Markus Hanselmann, Holger Ulmer, Katharina Dormann, Thilo Strauss, Andrej Junginger, Jens Stefan Buchner, Sebastian Boblest