PCF-GAN: generating sequential data via the characteristic function of measures on the path space

arXiv:2305.12511v2 Announce Type: replace
Abstract: Generating high-fidelity time series data using generative adversarial networks (GANs) remains a challenging task, as it is difficult to capture the temporal dependence of joint probability distributions induced by time-series data. Towards this goal, a key step is the development of an effective discriminator to distinguish between time series distributions. We propose the so-called PCF-GAN, a novel GAN that incorporates the path characteristic function (PCF) as the principled representation of time series distribution into the …

arxiv cs.lg data function gan path space type via