Machine-generated text is increasingly difficult to distinguish from text authored by humans.
Powerful open-source models are freely available, and user-friendly tools that democratize …

Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …

Heterogeneous tabular data are the most commonly used form of data and are essential for
numerous critical and computationally demanding applications. On homogeneous datasets …

Over the last several years, the field of natural language processing has been propelled
forward by an explosion in the use of deep learning models. This article provides a brief …

Background The electrocardiogram (ECG) is one of the most commonly used diagnostic
tools in medicine and healthcare. Deep learning methods have achieved promising results …

Generative adversarial network (GANs) is one of the most important research avenues in the
field of artificial intelligence, and its outstanding data generation capacity has received wide …

The Generative Models have gained considerable attention in unsupervised learning via a
new and practical framework called Generative Adversarial Networks (GAN) due to their …

We introduce Texygen, a benchmarking platform to support research on open-domain text
generation models. Texygen has not only implemented a majority of text generation models …

Automatically generating coherent and semantically meaningful text has many applications
in machine translation, dialogue systems, image captioning, etc. Recently, by combining …

Deep learning methods possess many processing layers to understand the stratified
representation of data and have achieved state-of-art results in several domains. Recently …