In the last two decades, network science has blossomed and influenced various fields, such
as statistical physics, computer science, biology and sociology, from the perspective of the …

Percolation is an emblematic model to assess the robustness of interconnected systems
when some of their components are corrupted. It is usually investigated in simple scenarios …

Diverse real world systems can be abstracted as complex networks consisting of nodes and
edges as functional components. Percolation theory has shown that the failure of a few of …

Can we employ one neural model to efficiently dismantle many complex yet unique
networks? This article provides an affirmative answer. Diverse real-world systems can be …

Nearly all real-world networks are complex networks and usually are in danger of collapse.
Therefore, it is crucial to exploit and understand the mechanisms of network attacks and …

The identification and rank of crucial spreaders aim to survey the diffusion capability, which
has a significant impact on controlling information spread in networks. However, most of the …

We propose a bond-percolation model intended to describe the consumption, and eventual
exhaustion, of resources in transport networks. Edges forming minimum-length paths …

Percolation models shed a light on network integrity and functionality and have numerous
applications in network theory. This paper studies a targeted percolation (α model) with …

In collaboration networks, a stable structure can lead to trust and enhance group members'
ties, in turn reducing conflicts and promoting communication and cooperation. Therefore …

Although robustness of connectivity and modular structures in networks have been attracted
much attentions in complex networks, most researches have focused on those two features …