Patents by Inventor Vignesh Ramanathan

Vignesh Ramanathan 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: 20240378590
    Abstract: Disclosed embodiments include a system for virtual card decline notifications. The system receives declination data regarding a first transaction using a prefunded virtual card. The system determines a reason the prefunded virtual card was declined using rules-based decisioning. The system categorizes the reason into one of one or more predetermined categories.
    Type: Application
    Filed: May 11, 2023
    Publication date: November 14, 2024
    Inventors: Vignesh Ramanathan, Kevin Sweet
  • Patent number: 10602207
    Abstract: An online system receives content items from a third party content provider. For each content item, the online system inputs an image into a neural network and extracts a feature vector from a hidden layer of the neural network. The online system compresses each feature vector by assigning a label to each feature value representing whether the feature value was above a threshold value. The online system identifies a set of content items that the user has interacted with and determines a user feature vector by aggregating feature vectors of the set of content items. For a new set of content items, the online system compares the compressed feature vectors of the content item with the user feature vector. The online system selects one or more of the new content items based on the comparison and sends the selected content items to the user.
    Type: Grant
    Filed: August 3, 2018
    Date of Patent: March 24, 2020
    Assignee: Facebook, Inc.
    Inventors: Tianshi Gao, Xiangyu Wang, Ou Jin, Yifei Huang, Vignesh Ramanathan
  • Publication number: 20200045354
    Abstract: An online system receives content items from a third party content provider. For each content item, the online system inputs an image into a neural network and extracts a feature vector from a hidden layer of the neural network. The online system compresses each feature vector by assigning a label to each feature value representing whether the feature value was above a threshold value. The online system identifies a set of content items that the user has interacted with and determines a user feature vector by aggregating feature vectors of the set of content items. For a new set of content items, the online system compares the compressed feature vectors of the content item with the user feature vector. The online system selects one or more of the new content items based on the comparison and sends the selected content items to the user.
    Type: Application
    Filed: August 3, 2018
    Publication date: February 6, 2020
    Inventors: Tianshi Gao, Xiangyu Wang, Ou Jin, Yifei Huang, Vignesh Ramanathan