Modern AI \textit{versus} century-old mathematical models: how far can we go with generative adversarial networks to reproduce stochastic processes?

DOI10.1016/J.PHYSD.2023.133831MaRDI QIDQ6111930

Pedro Lencastre, Anis Yazidi, Leonardo Rydin Gorjão, Marit Gjersdal, Pedro G. Lind

Publication date: 4 August 2023

Published in: Physica D (Search for Journal in Brave)

zbMATH Keywords

Markov modelstime-series predictiongenerative adversarial networksGANseye-tracking data

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

Cites Work

• Quant GANs: deep generation of financial time series
• An Introduction to Variational Autoencoders
• Unnamed Item

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