On the causality-preservation capabilities of generative modelling

DOI10.1016/j.cam.2024.116312MaRDI QIDQ6653565

Jan Dhaene, Milan van den Heuvel, Yves-Cédric Bauwelinckx, Tim Verdonck

Publication date: 16 December 2024

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

zbMATH Keywords

causalitydata scienceshortcutsynthetic datagenerative adversarial networksgenerative modelling

Mathematics Subject Classification ID

Artificial intelligence (68Txx) Actuarial science and mathematical finance (91Gxx) Multivariate analysis (62Hxx)

Cites Work

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• Estimation of causal effects using linear non-Gaussian causal models with hidden variables
• The curse of dimensionality in inverse problems
• Quant GANs: deep generation of financial time series
• Distributionally robust unsupervised domain adaptation
• Sig‐Wasserstein GANs for conditional time series generation

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