Mechanical metamaterials are meticulously designed structures with exceptional
mechanical properties determined by their microstructures and constituent materials …

Deep learning techniques, in particular generative models, have taken on great importance
in medical image analysis. This paper surveys fundamental deep learning concepts related …

As one of the representative unsupervised data augmentation methods, generative
adversarial networks (GANs) have the potential to solve the problem of insufficient samples …

Simple Summary The rapidly advancing field of deep learning, specifically transformer-
based architectures and attention mechanisms, has found substantial applicability in …

Generative Adversarial Networks (GANs) is a novel class of deep generative models that
has recently gained significant attention. GANs learn complex and high-dimensional …

The coronavirus (COVID-19) pandemic is putting healthcare systems across the world under
unprecedented and increasing pressure according to the World Health Organization (WHO) …

While hypothesis testing is a highly formalized activity, hypothesis generation remains
largely informal. We propose a systematic procedure to generate novel hypotheses about …

Image-to-image translation with generative adversarial networks (GANs) has been
extensively studied in recent years. Among the models, StarGAN has achieved image-to …

Abstract Generative Adversarial Networks (GANs) have been extremely successful in
various application domains such as computer vision, medicine, and natural language …

As typical mechanical metamaterials with negative Poisson's ratios, auxetic metamaterials
exhibit counterintuitive auxetic behaviors that are highly dependent on their geometric …