A signed network is a network in which each link is associated with a positive or negative
sign. Models for nodes interacting over such signed networks arise from various biological …

Abstract The 17 United Nations Sustainable Development Goals (SDGs) are set to change
the way we live, and aim to create, by 2030, a sustainable future balancing equitable …

Deep learning's performance has been extensively recognized recently. Graph neural
networks (GNNs) are designed to deal with graph-structural data that classical deep …

This work considers the robustness of uncertain consensus networks. The stability
properties of consensus networks with negative edge weights are also examined. We show …

We consider a nonlinear flow on simplicial complexes related to the simplicial Laplacian and
show that it is a generalization of various consensus and synchronization models commonly …

In this paper, we investigate a general nonlinear model of opinion dynamics in which both
state-dependent susceptibility to persuasion and antagonistic interactions are considered …

This work explores the definiteness of the weighted graph Laplacian matrix with negative
edge weights. The definiteness of the weighted Laplacian is studied in terms of certain …

In this paper, we consider bipartite tracking of linear multi-agent systems with a leader. Both
homogeneous and heterogeneous systems are investigated. The communication between …

This paper investigates the robustness of consensus protocols over weighted directed
graphs using the Nyquist criterion and small gain theorem for agents with single and double …

Signed graphs have appeared in a broad variety of applications, ranging from social
networks to biological networks, from distributed control and computation to power systems …