Coupled biological and chemical systems, neural networks, social interacting species, the
Internet and the World Wide Web, are only a few examples of systems composed by a large …

How does the Web look? How could we tell an abnormal social network from a normal one?
These and similar questions are important in many fields where the data can intuitively be …

Designing expressive Graph Neural Networks (GNNs) is a central topic in learning graph-
structured data. While numerous approaches have been proposed to improve GNNs in …

This book deals with the analysis of the structure of complex networks by combining results
from graph theory, physics, and pattern recognition. The book is divided into two parts. 11 …

Every branch of mathematics employs some notion of a product that enables the com-
bination or decomposition of its elemental structures. In graph theory there are four main …

We consider several well-studied problems in dynamic algorithms and prove that sufficient
progress on any of them would imply a breakthrough on one of five major open problems in …

The theory of directed graphs has developed enormously over recent decades, yet this book
(first published in 2000) remains the only book to cover more than a small fraction of the …

'Network'is a heavily overloaded term, so that 'network analysis' means different things to
different people. Specific forms of network analysis are used in the study of diverse …

Efficient join processing is one of the most fundamental and well-studied tasks in database
research. In this work, we examine algorithms for natural join queries over many relations …

We present a new randomized method for computing the min-plus product (aka, tropical
product) of two n× n matrices, yielding a faster algorithm for solving the all-pairs shortest …