Autoencoders and Generative Adversarial Networks for Imbalanced Sequence Classification

Stephanie Ger, Yegna Subramanian Jambunath, Diego Klabjan

Generative Adversarial Networks (GANs) have been used in many different applications to generate realistic synthetic data. We introduce a novel GAN with Autoencoder (GAN-AE) archit…