Patents by Inventor Mohak Saxena

Mohak Saxena 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).

  • SYSTEMS AND METHODS FOR USING MACHINE LEARNING WITH EPIDEMIOLOGICAL MODELING
    Publication number: 20230051833
    Abstract: Systems and methods of epidemiological modeling using machine learning are provided, and can include receiving values for an occurrence of the infectious disease during a first time period, generating, from a model trained by a machine learning system, predictions for the occurrence of the infectious disease over a second time period, performing, by a simulator using the predictions, one or more simulations of the occurrence of the infectious disease in one or more geographic regions during one or more time periods subsequent to the second time period, and providing, to a user interface, a first simulation of the one or more simulations performed by the simulator for a first geographic region of the one or more geographic regions during a time period of the one or more time periods.
    Type: Application
    Filed: July 28, 2022
    Publication date: February 16, 2023
    Applicant: DataRobot, Inc.
    Inventors: Jeremy Achin, Michael Schmidt, Mackenzie Heiser, Jona Sassenhagen, Oleg Baranovskiy, Jared Shamwell, Hon Nian Chua, Joao Paulo Gomes, Maxence Jeunesse, Yung Siang Liau, Julian Wergieluk, Jay Cameron Schuren, Mark Steadman, Mohak Saxena, Samuel Clark, Noa Flaherty, Jarred Bultema, Nathan Robert Cameron, Amanda Schierz, Vinay Venkata Wunnava, Xavier Conort, Gregory Michaelson, Anton Suslov, Madeleine Mott, Sergey Yurgenson, Christopher James Monsour, Matthew Joseph Nitzken, Patrick Allen Farrell, Jared Bowns, Dustin Burke, Ievgenii Baliuk, Rishabh Raman
  • Systems and methods for machine learning model interpretation
    Patent number: 11514369
    Abstract: Systems and methods are described for interpreting machine learning model predictions. An example method includes: providing a machine learning model configured to receive a plurality of features as input and provide a prediction as output, wherein the plurality of features includes an engineered feature including a combination of two or more parent features; calculating a Shapley value for each feature in the plurality of features; and allocating a respective portion of the Shapley value for the engineered feature to each of the two or more parent features.
    Type: Grant
    Filed: June 11, 2021
    Date of Patent: November 29, 2022
    Assignee: DataRobot, Inc.
    Inventors: Mark Benjamin Romanowsky, Jared Bowns, Thomas Whitehead, Thomas Stearns, Xavier Conort, Anastasiia Tamazlykar, Mohak Saxena
  • SYSTEMS AND METHODS FOR USING MACHINE LEARNING WITH EPIDEMIOLOGICAL MODELING
    Publication number: 20220199266
    Abstract: Systems and methods of epidemiological modeling using machine learning are provided, and can include receiving values for an occurrence of the infectious disease during a first time period, generating, from a model trained by a machine learning system, predictions for the occurrence of the infectious disease over a second time period, performing, by a simulator using the predictions, one or more simulations of the occurrence of the infectious disease in one or more geographic regions during one or more time periods subsequent to the second time period, and providing, to a user interface, a first simulation of the one or more simulations performed by the simulator for a first geographic region of the one or more geographic regions during a time period of the one or more time periods.
    Type: Application
    Filed: December 9, 2021
    Publication date: June 23, 2022
    Applicant: DataRobot, Inc.
    Inventors: Jeremy Achin, Earl Jared Shamwell, Michael Schmidt, Mackenzie Heiser, Patrick Farrell, Matt Nitzken, Jared Bowns, Nathan Cameron, Adam Beairsto, Jay Schuren, Mohak Saxena
  • SYSTEMS AND METHODS FOR MACHINE LEARNING MODEL INTERPRETATION
    Publication number: 20210390457
    Abstract: Systems and methods are described for interpreting machine learning model predictions. An example method includes: providing a machine learning model configured to receive a plurality of features as input and provide a prediction as output, wherein the plurality of features includes an engineered feature including a combination of two or more parent features; calculating a Shapley value for each feature in the plurality of features; and allocating a respective portion of the Shapley value for the engineered feature to each of the two or more parent features.
    Type: Application
    Filed: June 11, 2021
    Publication date: December 16, 2021
    Inventors: Mark Benjamin Romanowsky, Jared Bowns, Thomas Whitehead, Thomas Stearns, Xavier Conort, Anastasiia Tamazlykar, Mohak Saxena