Synthetic Data Generation for the Financial Industry Using Generative Adversarial Networks

Synthetic Data Generation for the Financial Industry Using Generative Adversarial Networks

Following the introduction of new laws and regulations to ensure data protection in GDPR and PIPEDA, interests in technologies to protect data privacy have increased. A promising research trajectory in this area is found in Generative Adversarial Networks (GAN), an architecture trained to produce da...

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Bibliographic Details
Main Author: Ljung, Mikael
Format: Others
Language:English
Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2021
Subjects:
Deep Learning
Generative Models
GAN
CTGAN
Synthetic Data
Financial Industry
Djupinlärning
generativ modellering
Syntetisk Data
Finansindustrin
Computer and Information Sciences
Data- och informationsvetenskap
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301307

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301307

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