This paper introduces a generalization of Convolutional Neural Networks (CNNs) to graphs
with irregular linkage structures, especially heterogeneous graphs with typed nodes and …

Understanding how animal movements change across space and time is a fundamental
question in ecology. While classical analyses of trajectories give insightful descriptors of …

Most previous studies of functional brain networks have been conducted on undirected
networks despite the fact that direction of information flow is able to provide additional …

The subject and main areas of a new research field—cybernetical physics—are discussed.
A brief history of cybernetical physics is outlined. The main areas of activity in cybernetical …

Understanding the control of gene expression remains one of the main challenges in the
post-genomic era. Accordingly, a plethora of methods exists to identify variations in gene …

Modelling 3D objects in CAD software requires special skills which require a novice user to
undergo a series of training exercises to obtain. To minimize the training time for a novice …

In this book we describe a large number of open problems in the theory of stochastic neural
systems, with the aim of enticing probabilists to work on them. These include problems …

This paper presents two novel network methods developed for education research. These
methods were used to investigate online discussions and the structure of students' …

Lately, new materialism has been proposed as a theoretical framework to better understand
material-dialogic relationships in learning, and concurrently network analysis has emerged …

Counting motifs in an uncertain graph for which each link is associated with a connection
probability is computationally expensive when the graph is huge due to the extremely large …