activity
20192026
most citedIdentifying vital nodes by Achlioptas process

30 citations · 37 across the 5 of their papers we have counts for

collaborators

9 papers

cs.SI20261 cited

FS_GPlib: Breaking the Web-Scale Barrier - A Unified Acceleration Framework for Graph Propagation Models

Chang Guo, Juyuan Zhang, Chang Su +2

Propagation models are essential for modeling and simulating dynamic processes such as epidemics and information diffusion. However, existing tools struggle to scale to large-scale…

cs.SI2025

Structure-Aware Optimal Intervention for Rumor Dynamics on Networks: Node-Level, Time-Varying, and Resource-Constrained

Yan Zhu, Qingyang Liu, Chang Guo +2

Rumor propagation in social networks undermines social stability and public trust, calling for interventions that are both effective and resource-efficient. We develop a node-level…

cs.SI2025

Deterministic Frequency--Domain Inference of Network Topology and Hidden Components via Structure--Behavior Scaling

Xiaoxiao Liang, Tianlong Fan, Linyuan Lü

Hidden interactions and components in complex systems-ranging from covert actors in terrorist networks to unobserved brain regions and molecular regulators-often manifest only thro…

eess.SY2025

Revealing Chaotic Dependence and Degree-Structure Mechanisms in Optimal Pinning Control of Complex Networks

Qingyang Liu, Tianlong Fan, Liming Pan +1

Identifying an optimal set of driver nodes to achieve synchronization via pinning control is a fundamental challenge in complex network science, limited by computational intractabi…

eess.SY2025

Perturbation-Based Pinning Control Strategy for Enhanced Synchronization in Complex Networks

Ziang Mao, Tianlong Fan, Linyuan Lü

Synchronization is essential for the stability and coordinated operation of complex networked systems. Pinning control, which selectively controls a subset of nodes, provides a sca…

cs.SI2025

Weighted cycle-based identification of influential node groups in complex networks

Wenxin Zheng, Wenfeng Shi, Tianlong Fan +1

Identifying influential node groups in complex networks is crucial for optimizing information dissemination, epidemic control, and viral marketing. However, traditional centrality-…