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:
Apr. 01, 2025

Filed:

May. 11, 2021
Applicant:

Capital One Services, Llc, McLean, VA (US);

Inventors:

Jeremy Goodsitt, Champaign, IL (US);

Austin Walters, Savoy, IL (US);

Vincent Pham, Champaign, IL (US);

Fardin Abdi Taghi Abad, Seattle, WA (US);

Assignee:

Capital One Services, LLC, McLean, VA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 18/2413 (2023.01); G06N 3/02 (2006.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 18/24143 (2023.01); G06N 3/02 (2013.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01); G06N 3/044 (2023.01);
Abstract

Systems and methods for generating synthetic intercorrelated data are disclosed. For example, a system may include at least one memory storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include training a parent model by iteratively performing steps. The steps may include generating, using the parent model, first latent-space data and second latent-space data. The steps may include generating, using a first child model, first synthetic data based on the first latent-space data, and generating, using a second child model, second synthetic data based on the second latent-space data. The steps may include comparing the first synthetic data and second synthetic data to training data. The steps may include adjusting a parameter of the parent model based on the comparison or terminating training of the parent model based on the comparison.


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