The dynamic neural network (DNN), in contrast to the static counterpart, offers numerous
advantages, such as improved accuracy, efficiency, and interpretability. These benefits stem …

Temporal graph learning aims to generate high-quality representations for graph-based
tasks with dynamic information, which has recently garnered increasing attention. In contrast …

Influence maximization (IM) is a widely investigated issue in the study of social networks
because of its potential commercial and social value. The purpose of IM is to identify a group …

With the prosperity of modern technology, propagation phenomena of diverse information
become universal nowadays. Nevertheless, spreading of malicious information will …

In recent years, multilayer networks have served as effective models for addressing and
analyzing real-world systems with multiple relationships. Among these scenarios, the …

Medication combination prediction (MCP) can provide assistance for experts in the more
thorough comprehension of complex mechanisms behind health and disease. Many recent …

This paper proposes an adaptive fuzzy output feedback control approach for quadrotor
unmanned aerial vehicles (QUAV) with stochastic disturbances, besides which we consider …

Recently, deep neural networks (DNNs) have been widely used in hyperspectral image
change detection (HSI-CD). Generally, training such a DNN-based HSI-CD network often …

Understanding the feedback loop that links the spatiotemporal spread of infectious diseases
and human behavior is an open problem. To study this problem, we develop a multiplex …

With the continuous development of technology and networks, real-life interactions are
gradually being abstracted into social networks for study. Social circles are a fundamental …