We investigate disease spreading on eight empirical data sets of human contacts (mostly proximity networks recording who is close to whom, at what time). We compare three levels of representations of these data sets: temporal networks, static networks, and a fully connected topology. We notice that the difference between the static and fully connected networks-with respect to time to extinction...

In this article we give an in depth overview of the recent advances in the field of equilibrium networks. After outlining this topic, we provide a novel way of defining equilibrium graph (network) ensembles. We illustrate this concept on the classical random graph model and then survey a large variety of recently studied network models. Next, we analyze the structural properties of the graphs i...

Bayesian Network structures with a maximum in-degree of k can be approximated with respect to a positive scoring metric up to an factor of 1/k.

Network Analysis is employed as methodological approach to classify social roles. With this aim, we measure sociometric status by the direct observation of pre-school children behaviours. The data have been collected by a longitudinal observational study. We follow the children in seven waves for two months. In this study, we measure relational skills of subjects applying three procedures. Name...

Geometric and structural constraints greatly restrict the selection of folds adapted by protein backbones, and yet, folded proteins show an astounding diversity in functionality. For structure to have any bearing on function, it is thus imperative that, apart from the protein backbone, other tunable degrees of freedom be accountable. Here, we focus on side-chain interactions, which non-covalent...

The structure and operation of supply networks have received considerable attention from both the business community and academic researchers in the last two decades as the pace of globalisation has accelerated. Supply networks in the international clothing industry have developed and evolved significantly over that period. This paper reviews different ways to categorise supply networks and not...

OF THE DISSERTATION Cultural Consensus Theory on Network Structures By Kalin Alak Agrawal Doctor of Philosophy in Mathematical Behavioral Sciences University of California, Irvine, 2015 Professor William H. Batchelder, Chair Cultural Consensus Theory (CCT) consists of cognitive models for aggregating the responses of informants to test items about some domain of their shared cultural knowledge....

Bayesian networks (BNs) are directed graphical models that have been widely used in various tasks for probabilistic reasoning and causal modeling. One major challenge in these tasks is to learn the BN structures from data. In this paper, we propose a novel heuristic algorithm for BN structure learning that takes advantage of the idea of curriculum learning. Our algorithm learns the BN structure...