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Financial Time Series Data Augmentation with Generative Adversarial Networks and extended Intertemporal Return Plots. (arXiv:2205.08924v1 [cs.CV])
cs.CV updates on arXiv.org arxiv.org
Data augmentation is a key regularization method to support the forecast and
classification performance of highly parameterized models in computer vision.
In the time series domain however, regularization in terms of augmentation is
not equally common even though these methods have proven to mitigate effects
from small sample size or non-stationarity. In this paper we apply state-of-the
art image-based generative models for the task of data augmentation and
introduce the extended intertemporal return plot (XIRP), a new image
representation for …
arxiv augmentation cv data financial generative adversarial networks networks series time time series