Signal propagation in complex networks drives epidemics, is responsible for information
going viral, promotes trust and facilitates moral behavior in social groups, enables the …

With the increasing demand for intelligent services, the sixth-generation (6G) wireless
networks will shift from a traditional architecture that focuses solely on a high transmission …

Seismic waves from earthquakes and other sources are used to infer the structure and
properties of Earth's interior. The availability of large-scale seismic datasets and the …

The conjoining of dynamical systems and deep learning has become a topic of great
interest. In particular, neural differential equations (NDEs) demonstrate that neural networks …

Partial differential equations (PDEs) are among the most universal and parsimonious
descriptions of natural physical laws, capturing a rich variety of phenomenology and …

Controlling electromagnetic waves and information simultaneously by information
metasurfaces is of central importance in modern society. Intelligent metasurfaces are smart …

Dynamic mode decomposition (DMD) is a factorization and dimensionality reduction
technique for data sequences. In its most common form, it processes high-dimensional …

The advances of deep learning (DL) techniques bring new opportunities to numerous
intractable tasks in power systems (PSs). Nevertheless, the extension of the application of …

Abstract Machine learning is rapidly becoming a core technology for scientific computing,
with numerous opportunities to advance the field of computational fluid dynamics. Here we …

Despite great progress in simulating multiphysics problems using the numerical
discretization of partial differential equations (PDEs), one still cannot seamlessly incorporate …