Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …

Deep generative models have been an upsurge in the deep learning community since they
were proposed. These models are designed for generating new synthetic data including …

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a
driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted …

Graphs are important data representations for describing objects and their relationships,
which appear in a wide diversity of real-world scenarios. As one of a critical problem in this …

Graphs are ubiquitous in encoding relational information of real-world objects in many
domains. Graph generation, whose purpose is to generate new graphs from a distribution …

Diffusion models, as a novel generative paradigm, have achieved remarkable success in
various image generation tasks such as image inpainting, image-to-text translation, and …

Spider webs are incredible biological structures, comprising thin but strong silk filament and
arranged into complex hierarchical architectures with striking mechanical properties (eg …

Graph neural networks (GNNs) conduct feature learning by taking into account the local
structure preservation of the data to produce discriminative features, but need to address the …

Although there exist several libraries for deep learning on graphs, they are aiming at
implementing basic operations for graph deep learning. In the research community …

Designing and generating new data under targeted properties has been attracting various
critical applications such as molecule design, image editing and speech synthesis …