Networks (or graphs) appear as dominant structures in diverse domains, including
sociology, biology, neuroscience and computer science. In most of the aforementioned …

Many real-world relations can be represented by signed networks with positive and negative
links, as a result of which signed network analysis has attracted increasing attention from …

“Nature shows us only the tail of the lion. But I do not doubt that the lion belongs to it even
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …

In online social networks people often express attitudes towards others, which forms
massive sentiment links among users. Predicting the sign of sentiment links is a fundamental …

Due to the fact much of today's data can be represented as graphs, there has been a
demand for generalizing neural network models for graph data. One recent direction that …

In a consensus protocol an agreement among agents is achieved thanks to the collaborative
efforts of all agents, expresses by a communication graph with nonnegative weights. The …

Network embedding is to learn low-dimensional vector representations for nodes of a given
social network, facilitating many tasks in social network analysis such as link prediction. The …

Modern neuroimaging techniques provide us with unique views on brain structure and
function; ie, how the brain is wired, and where and when activity takes place. Data acquired …

Over the past two decades, epidemic spreading on complex network has been a vibrant and
highly successful research avenue. The dynamics of epidemic spreading on signed …

The aim of this paper is to address consensus and bipartite consensus for a group of
homogeneous agents, under the assumption that their mutual interactions can be described …