most citedAutoencoders and Generative Adversarial Networks for Imbalanced Sequence Classification

2 citations · 2 across the 1 of their papers we have counts for

collaborators

2 papers

cs.LG2021

Classification Models for Partially Ordered Sequences

Stephanie Ger, Diego Klabjan, Jean Utke

Many models such as Long Short Term Memory (LSTMs), Gated Recurrent Units (GRUs) and transformers have been developed to classify time series data with the assumption that events i…

cs.LG2019★ 2 cited

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…