Patents by Inventor Ekaterina Hristova Taralova

Ekaterina Hristova Taralova 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).

  • Tuning simulated data for optimized neural network activation
    Patent number: 11615223
    Abstract: Techniques described herein are directed to comparing, using a machine-trained model, neural network activations associated with data representing a simulated environment and activations associated with data representing real environment to determine whether the simulated environment is causes similar responses by the neural network, e.g., a detector. If the simulated environment and the real environment do not activate the same way (e.g., the variation between neural network activations of real and simulated data meets or exceeds a threshold), techniques described herein are directed to modifying parameters of the simulated environment to generate a modified simulated environment that more closely resembles the real environment.
    Type: Grant
    Filed: October 15, 2020
    Date of Patent: March 28, 2023
    Assignee: Zoox, Inc.
    Inventor: Ekaterina Hristova Taralova
  • TUNING SIMULATED DATA FOR OPTIMIZED NEURAL NETWORK ACTIVATION
    Publication number: 20210027111
    Abstract: Techniques described herein are directed to comparing, using a machine-trained model, neural network activations associated with data representing a simulated environment and activations associated with data representing real environment to determine whether the simulated environment is causes similar responses by the neural network, e.g., a detector. If the simulated environment and the real environment do not activate the same way (e.g., the variation between neural network activations of real and simulated data meets or exceeds a threshold), techniques described herein are directed to modifying parameters of the simulated environment to generate a modified simulated environment that more closely resembles the real environment.
    Type: Application
    Filed: October 15, 2020
    Publication date: January 28, 2021
    Inventor: Ekaterina Hristova Taralova
  • Tuning simulated data for optimized neural network activation
    Patent number: 10832093
    Abstract: Techniques described herein are directed to comparing, using a machine-trained model, neural network activations associated with data representing a simulated environment and activations associated with data representing real environment to determine whether the simulated environment is causes similar responses by the neural network, e.g., a detector. If the simulated environment and the real environment do not activate the same way (e.g., the variation between neural network activations of real and simulated data meets or exceeds a threshold), techniques described herein are directed to modifying parameters of the simulated environment to generate a modified simulated environment that more closely resembles the real environment.
    Type: Grant
    Filed: October 17, 2018
    Date of Patent: November 10, 2020
    Assignee: Zoox, Inc.
    Inventor: Ekaterina Hristova Taralova