Patents by Inventor Tomas J. Pfister

Tomas J. Pfister 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).

  • GENERATING REALISTIC SYNTHETIC DATA WITH ADVERSARIAL NETS
    Publication number: 20230081346
    Abstract: A generative network may be learned in an adversarial setting with a goal of modifying synthetic data such that a discriminative network may not be able to reliably tell the difference between refined synthetic data and real data. The generative network and discriminative network may work together to learn how to produce more realistic synthetic data with reduced computational cost. The generative network may iteratively learn a function that synthetic data with a goal of generating refined synthetic data that is more difficult for the discriminative network to differentiate from real data, while the discriminative network may be configured to iteratively learn a function that classifies data as either synthetic or real. Over multiple iterations, the generative network may learn to refine the synthetic data to produce refined synthetic data on which other machine learning models may be trained.
    Type: Application
    Filed: October 14, 2022
    Publication date: March 16, 2023
    Applicant: Apple Inc.
    Inventors: Ashish Shrivastava, Tomas J. Pfister, Cuneyt O. Tuzel, Russell Y. Webb, Joshua Matthew Susskind
  • Generating more realistic synthetic data with adversarial nets
    Patent number: 11475276
    Abstract: A generative network may be learned in an adversarial setting with a goal of modifying synthetic data such that a discriminative network may not be able to reliably tell the difference between refined synthetic data and real data. The generative network and discriminative network may work together to learn how to produce more realistic synthetic data with reduced computational cost. The generative network may iteratively learn a function that synthetic data with a goal of generating refined synthetic data that is more difficult for the discriminative network to differentiate from real data, while the discriminative network may be configured to iteratively learn a function that classifies data as either synthetic or real. Over multiple iterations, the generative network may learn to refine the synthetic data to produce refined synthetic data on which other machine learning models may be trained.
    Type: Grant
    Filed: November 6, 2017
    Date of Patent: October 18, 2022
    Assignee: Apple Inc.
    Inventors: Ashish Shrivastava, Tomas J. Pfister, Cuneyt O. Tuzel, Russell Y. Webb, Joshua Matthew Susskind
  • Intelligent software agent
    Patent number: 11437039
    Abstract: Modifying operation of an intelligent agent in response to facial expressions and/or emotions.
    Type: Grant
    Filed: December 23, 2020
    Date of Patent: September 6, 2022
    Inventors: Siddharth Khullar, Abhishek Sharma, Jerremy Holland, Nicholas E. Apostoloff, Russell Y. Webb, Tai-Peng Tian, Tomas J. Pfister
  • Intelligent Software Agent
    Publication number: 20210166691
    Abstract: Modifying operation of an intelligent agent in response to facial expressions and/or emotions.
    Type: Application
    Filed: December 23, 2020
    Publication date: June 3, 2021
    Inventors: Siddharth Khullar, Abhishek Sharma, Jerremy Holland, Nicholas E. Apostoloff, Russell Y. Webb, Tai-Peng Tian, Tomas J. Pfister
  • Intelligent software agent
    Patent number: 10885915
    Abstract: Modifying operation of an intelligent agent in response to facial expressions and/or emotions.
    Type: Grant
    Filed: June 30, 2017
    Date of Patent: January 5, 2021
    Inventors: Siddharth Khullar, Abhishek Sharma, Jerremy Holland, Nicholas E. Apostoloff, Russell Y. Webb, Tai-Peng Tian, Tomas J. Pfister
  • Intelligent Software Agent
    Publication number: 20190348037
    Abstract: Modifying operation of an intelligent agent in response to facial expressions and/or emotions.
    Type: Application
    Filed: June 30, 2017
    Publication date: November 14, 2019
    Inventors: Siddharth Khullar, Abhishek Sharma, Jerremy Holland, Nicholas E. Apostoloff, Russell Y. Webb, Tai-Peng Tian, Tomas J. Pfister