Abstract Information cascade size prediction is one of the primary challenges for
understanding the diffusion of information. Traditional feature‐based methods heavily rely …

Remote sensing scene classification has gained increasing interest in remote sensing
image understanding and feature representation is the crucial factor for classification …

Efficient numerical linear algebra is a core ingredient in many applications across almost all
scientific and industrial disciplines. With this survey we want to illustrate that numerical linear …

Motivation Malaria, a mosquito-borne infectious disease affecting humans and other
animals, is widespread in tropical and subtropical regions. Microscopy is the most common …

Many graph representation learning (GRL) problems are dynamic, with millions of edges
added or removed per second. A fundamental workload in this setting is dynamic link …

Abstract Knowledge graphs (KGs) have recently become increasingly popular due to the
broad range of essential applications in various downstream tasks including intelligent …

-truss model is a typical cohesive subgraph model and has been received considerable
attention recently. However, the-truss model only considers the direct common neighbors of …

Graph attention networks (GATs) have been shown effectively for representation learning.
However, existing GATs only employ the first-order attention mechanism and thus fail to fully …

As social networks become indispensable for people's daily lives, inference attacks pose
significant threat to users' privacy where attackers can infiltrate users' information and infer …

RNA-binding proteins (RBPs) are a class of proteins with RNA-binding domains involved in
regulating various cellular processes, such as RNA processing, transport, splicing …