US 12,265,894 B2
Hierarchical system and method for generating intercorrelated datasets
Jeremy Goodsitt, Champaign, IL (US); Austin Walters, Savoy, IL (US); Vincent Pham, Champaign, IL (US); and Fardin Abdi Taghi Abad, Seattle, WA (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by CAPITAL ONE SERVICES, LLC, McLean, VA (US)
Filed on May 11, 2021, as Appl. No. 17/317,010.
Application 17/317,010 is a continuation of application No. 16/748,415, filed on Jan. 21, 2020, granted, now 11,030,526.
Prior Publication US 2021/0264277 A1, Aug. 26, 2021
Int. Cl. 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)
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)] 20 Claims
OG exemplary drawing
 
1. A system for generating synthetic intercorrelated data, the system comprising:
one or more memory units for storing instructions; and
one or more processors configured to execute the instructions to perform operations comprising:
receiving a plurality of intercorrelated datasets;
extracting individual ones of the plurality of intercorrelated datasets;
generating latent-space data using a parent model; and
training child models to generate synthetic data based on the latent-space data and the extracted intercorrelated-datasets.