Patents by Inventor Shashank Shailabh

Shashank Shailabh 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).

  • System and methods for neural topic modeling using topic attention networks
    Patent number: 12190061
    Abstract: Systems and methods for topic modeling are described. The systems and methods include encoding words of a document using an embedding matrix to obtain word embeddings for the document. The words of the document comprise a subset of words in a vocabulary, and the embedding matrix is trained as part of a topic attention network based on a plurality of topics. The systems and methods further include encoding a topic-word distribution matrix using the embedding matrix to obtain a topic embedding matrix. The topic-word distribution matrix represents relationships between the plurality of topics and the words of the vocabulary. The systems and methods further include computing a topic context matrix based on the topic embedding matrix and the word embeddings and identifying a topic for the document based on the topic context matrix.
    Type: Grant
    Filed: December 17, 2021
    Date of Patent: January 7, 2025
    Assignee: ADOBE INC.
    Inventors: Shashank Shailabh, Madhur Panwar, Milan Aggarwal, Pinkesh Badjatiya, Simra Shahid, Nikaash Puri, S Sejal Naidu, Sharat Chandra Racha, Balaji Krishnamurthy, Ganesh Karbhari Palwe
  • SYSTEM AND METHODS FOR NEURAL TOPIC MODELING USING TOPIC ATTENTION NETWORKS
    Publication number: 20230169271
    Abstract: Systems and methods for topic modeling are described. The systems and methods include encoding words of a document using an embedding matrix to obtain word embeddings for the document. The words of the document comprise a subset of words in a vocabulary, and the embedding matrix is trained as part of a topic attention network based on a plurality of topics. The systems and methods further include encoding a topic-word distribution matrix using the embedding matrix to obtain a topic embedding matrix. The topic-word distribution matrix represents relationships between the plurality of topics and the words of the vocabulary. The systems and methods further include computing a topic context matrix based on the topic embedding matrix and the word embeddings and identifying a topic for the document based on the topic context matrix.
    Type: Application
    Filed: December 17, 2021
    Publication date: June 1, 2023
    Inventors: Shashank Shailabh, Madhur Panwar, Milan Aggarwal, Pinkesh Badjatiya, Simra Shahid, Nikaash Puri, S Sejal Naidu, Sharat Chandra Racha, Balaji Krishnamurthy, Ganesh Karbhari Palwe