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US Patent 11669769 Conditioned synthetic data generation in computer-based reasoning systems

Patent 11669769 was granted and assigned to Diveplane on June, 2023 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
1

Patent attributes

Patent Applicant
Diveplane
Diveplane
1
Current Assignee
Diveplane
Diveplane
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
116697691
Date of Patent
June 6, 2023
1
Patent Application Number
170061441
Date Filed
August 28, 2020
1
Patent Citations
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US Patent 10991092 Magnetic resonance imaging quality classification based on deep machine-learning to account for less training data
1
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US Patent 10559299 Reconciliation between simulator and speech recognition output using sequence-to-sequence mapping
1
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US Patent 7873587 Method and system for creating a program to preform a desired task based on programs learned from other tasks
1
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US Patent 9443194 Missing value imputation for predictive models
1
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US Patent 9489635 Methods and systems for vehicle perception feedback to classify data representative of types of objects and to request feedback regarding such classifications
1
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US Patent 10382799 Real-time synthetically generated video from still frames
1
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US Patent 10459444 Autonomous vehicle fleet model training and testing
1
Patent Citations Received
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US Patent 12008446 Conditioned synthetic data generation in computer-based reasoning systems
2
Patent Primary Examiner
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Moustafa M Meky
1
CPC Code
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G06N 5/04
1
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G06N 20/00
1
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G06F 16/2282
1

Techniques for synthetic data generation in computer-based reasoning systems are discussed and include receiving a request for generation of synthetic data based on a set of training data cases. One or more focal training data cases are determined. For undetermined features (either all of them or those that are not subject to conditions), a value for the feature is determined based on the focal cases. In some embodiments, the generation of synthetic data may be conditioned on values of features, preserved features, such as unique identifiers, previous-in-time features, and using the other techniques discussed herein.

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