Patents by Inventor Matthew Chase Fulp

Matthew Chase Fulp 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).

  • Publication number: 20240386323
    Abstract: Techniques for synthetic data generation in computer-based reasoning systems are discussed and include receiving a request for generation of synthetic data based on a set of training data cases. One or more focal training data cases are determined. For undetermined features (either all of them or those that are not subject to conditions), a value for the feature is determined based on the focal cases. In some embodiments, the generation of synthetic data may be conditioned on values of features, preserved features, such as unique identifiers, previous-in-time features, and using the other techniques discussed herein.
    Type: Application
    Filed: April 30, 2024
    Publication date: November 21, 2024
    Inventors: Christopher James Hazard, Michael Resnick, Ravisutha Sakrepatna Srinivasamurthy, David R. Cheeseman, Valeri A. Korobov, Martin James Koistinen, Matthew Chase Fulp
  • Patent number: 12008446
    Abstract: Techniques for synthetic data generation in computer-based reasoning systems are discussed and include receiving a request for generation of synthetic data based on a set of training data cases. One or more focal training data cases are determined. For undetermined features (either all of them or those that are not subject to conditions), a value for the feature is determined based on the focal cases. In some embodiments, the generation of synthetic data may be conditioned on values of features, preserved features, such as unique identifiers, previous-in-time features, and using the other techniques discussed herein.
    Type: Grant
    Filed: October 24, 2022
    Date of Patent: June 11, 2024
    Assignee: Howso Incorporated
    Inventors: Christopher James Hazard, Michael Resnick, Ravisutha Sakrepatna Srinivasamurthy, David R. Cheeseman, Valeri A. Korobov, Martin James Koistinen, Matthew Chase Fulp
  • Patent number: 11669769
    Abstract: Techniques for synthetic data generation in computer-based reasoning systems are discussed and include receiving a request for generation of synthetic data based on a set of training data cases. One or more focal training data cases are determined. For undetermined features (either all of them or those that are not subject to conditions), a value for the feature is determined based on the focal cases. In some embodiments, the generation of synthetic data may be conditioned on values of features, preserved features, such as unique identifiers, previous-in-time features, and using the other techniques discussed herein.
    Type: Grant
    Filed: August 28, 2020
    Date of Patent: June 6, 2023
    Assignee: Diveplane Corporation
    Inventors: Christopher James Hazard, Ravisutha Sakrepatna Srinivasamurthy, David R. Cheeseman, Valeri A. Korobov, Martin James Koistinen, Matthew Chase Fulp, Michael Resnick
  • Publication number: 20230140842
    Abstract: Techniques for synthetic data generation in computer-based reasoning systems are discussed and include receiving a request for generation of synthetic data based on a set of training data cases. One or more focal training data cases are determined. For undetermined features (either all of them or those that are not subject to conditions), a value for the feature is determined based on the focal cases. In some embodiments, the generation of synthetic data may be conditioned on values of features, preserved features, such as unique identifiers, previous-in-time features, and using the other techniques discussed herein.
    Type: Application
    Filed: August 28, 2020
    Publication date: May 4, 2023
    Inventors: Christopher James Hazard, Ravisutha Sakrepatna Srinivasamurthy, David R. Cheeseman, Valeri A. Korobov, Martin James Koistinen, Matthew Chase Fulp, Michael Resnick
  • Publication number: 20230046874
    Abstract: Techniques for synthetic data generation in computer-based reasoning systems are discussed and include receiving a request for generation of synthetic data based on a set of training data cases. One or more focal training data cases are determined. For undetermined features (either all of them or those that are not subject to conditions), a value for the feature is determined based on the focal cases. In some embodiments, the generation of synthetic data may be conditioned on values of features, preserved features, such as unique identifiers, previous-in-time features, and using the other techniques discussed herein.
    Type: Application
    Filed: October 24, 2022
    Publication date: February 16, 2023
    Inventors: Christopher James Hazard, Michael Resnick, Ravisutha Sakrepatna Srinivasamurthy, David R. Cheeseman, Valeri A. Korobov, Martin James Koistinen, Matthew Chase Fulp
  • Patent number: 11455557
    Abstract: Techniques for synthetic data generation in computer-based reasoning systems are discussed and include receiving a request for generation of synthetic data based on a set of training data cases. One or more focal training data cases are determined. For undetermined features (either all of them or those that are not subject to conditions), a value for the feature is determined based on the focal cases. In some embodiments, the generation of synthetic data may be conditioned on values of features, preserved features, such as unique identifiers, previous-in-time features, and using the other techniques discussed herein.
    Type: Grant
    Filed: August 28, 2020
    Date of Patent: September 27, 2022
    Assignee: Diveplane Corporation
    Inventors: Christopher James Hazard, Ravisutha Sakrepatna Srinivasamurthy, David R. Cheeseman, Valeri A. Korobov, Martin James Koistinen, Matthew Chase Fulp, Michael Resnick