The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 10, 2026

Filed:

Oct. 19, 2022
Applicants:

Emory University, Atlanta, GA (US);

The University of Chicago, Chicago, IL (US);

Georgia Tech Research Corporation, Atlanta, GA (US);

The University of North Carolina AT Chapel Hill, Chapel Hill, NC (US);

Inventors:

Chethan Pandarinath, Decatur, GA (US);

Feng Zhu, Atlanta, GA (US);

Matthew Tyler Kaufman, Chicago, IL (US);

Andrew Robert Sedler, Atlanta, GA (US);

Andrea Giovannucci, Chapel Hill, NC (US);

Assignees:

Emory University, Atlanta, GA (US);

The University of Chicago, Chicago, IL (US);

Georgia Tech Research Corporation, Atlanta, GA (US);

The University of North Carolina at Chapel Hill, Chapel Hill, NC (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 10/774 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06V 10/774 (2022.01); G06V 10/82 (2022.01);
Abstract

The present disclosure provides novel training systems and methods for recurrent neural network models. One such method comprises obtaining a first sequence of sparse input data as training data; augmenting the first sequence of sparse input data by zero-filling missing input points; training the recurrent neural network model using the augmented sequence of sparse input data to obtain a trained recurrent neural network model, and applying new data as an input to the trained recurrent neural network model, wherein the new data comprises a second sequence of sparse input data to obtain a corresponding output data sequence.


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Pandarinath, Chethan. (2026). Selective backpropagation through time (U.S. Patent No. 12793394). U.S. Patent and Trademark Office. https://idiyas.com/patent/badge/12793394

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