Computing subgraph frequencies is a fundamental task that lies at the core of several
network analysis methodologies, such as network motifs and graphlet-based metrics, which …

While Graph Neural Networks (GNNs) have achieved remarkable results in a variety of
applications, recent studies exposed important shortcomings in their ability to capture the …

Networks are a fundamental tool for understanding and modeling complex systems in
physics, biology, neuroscience, engineering, and social science. Many networks are known …

Ongoing advances in force field and computer hardware development enable the use of
molecular dynamics (MD) to simulate increasingly complex systems with the ultimate goal of …

Binary code similarity detection, which answers whether two pieces of binary code are
similar, has been used in a number of applications, such as vulnerability detection and …

We study the effects of municipal mergers using novel geocoded data on local public sector
jobs and local politicians' place of residence. We find that the mergers had no effects on …

Money laundering refers to the criminal attempt of concealing the origins of illegally obtained
money, usually by passing it through a complex sequence of seemingly legitimate financial …

Community detection (or graph clustering) is crucial for unraveling the structural properties
of complex networks. As an important technique in community detection, label propagation …

Subgraph matching is a fundamental problem in graph analysis. In recent years, many
subgraph matching algorithms have been proposed, making it pressing and challenging to …

Motivation Graphlets are a useful tool to determine a graph's small-scale structure. Finding
them is exponentially hard with respect to the number of nodes in each graphlet. Therefore …