Patents by Inventor Patrick George Flor

Patrick George Flor 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).

  • Forecasting demand using hierarchical temporal memory
    Patent number: 11816588
    Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media to forecast demand by implementing an online demand prediction framework that includes a hierarchical temporal memory network (HTM) configured to learn temporal patterns representing sequences of states of time-series data collected from a set of one or more data sources representing demand and input to the HTM. In some embodiments, the HTM learns the temporal patterns using a Cortical Learning Algorithm.
    Type: Grant
    Filed: December 23, 2019
    Date of Patent: November 14, 2023
    Assignee: Groupon, Inc.
    Inventors: Patrick George Flor, Dylan Griffith, Riva Ashley Vanderveld
  • Forecasting Demand Using Hierarchical Temporal Memory
    Publication number: 20200210870
    Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media to forecast demand by implementing an online demand prediction framework that includes a hierarchical temporal memory network (HTM) configured to learn temporal patterns representing sequences of states of time-series data collected from a set of one or more data sources representing demand and input to the HTM. In some embodiments, the HTM learns the temporal patterns using a Cortical Learning Algorithm.
    Type: Application
    Filed: December 23, 2019
    Publication date: July 2, 2020
    Inventors: Patrick George FLOR, Dylan Griffith, Riva Ashley Vanderveld
  • Forecasting demand using hierarchical temporal memory
    Patent number: 10558925
    Abstract: In general, embodiments of the present invention provide systems, methods and computer readable media to forecast demand by implementing an online demand prediction framework that includes a hierarchical temporal memory network (HTM) configured to learn temporal patterns representing sequences of states of time-series data collected from a set of one or more data sources representing demand and input to the HTM. In some embodiments, the HTM learns the temporal patterns using a Cortical Learning Algorithm.
    Type: Grant
    Filed: March 27, 2015
    Date of Patent: February 11, 2020
    Assignee: GROUPON, INC.
    Inventors: Patrick George Flor, Dylan Griffith, Riva Ashley Vanderveld