Our recent paper [Grauwin et al. Sci. Rep. 7 (2017)] demonstrates that community and hierarchical structure of the networks of human interactions largely determines the least and should be taken into account while modeling them. In the present proof-of-concept pre-print the opposite question is considered: could the hierarchical structure itself be inferred to be best aligned with the network m...

Robust network design refers to a class of optimization problems that occur when designing networks to efficiently handle variable demands. The notion of “hierarchical hubbing” was introduced (in the narrow context of a specific robust network design question), by Olver and Shepherd [14]. Hierarchical hubbing allows for routings with a multiplicity of “hubs” which are connected to the terminals...

We propose a novel hierarchical generative model with a simple Markovian structure and a corresponding inference model. Both the generative and inference model are trained using the adversarial learning paradigm. We demonstrate that the hierarchical structure supports the learning of progressively more abstract representations as well as providing semantically meaningful reconstructions with di...

We introduce a growing network model which generates both modular and hierarchical structure in a self-organized way. To this end, we modify the Barabási–Albert model into the one evolving under the principles of division and independence as well as growth and preferential attachment (PA). A newly added vertex chooses one of the modules composed of existing vertices, and attaches edges to verti...

The advent of a new kind entangled state known as hybrid state, i.e., entanglement between different degrees freedom, makes it possible to perform various quantum computational and communication tasks with lesser amount resources. Here, we aim exploit the advantage these states in over networks. Unfortunately, shared network deteriorates due its unavoidable interaction surroundings. Thus, an co...

This article describes a model based approach to designing network intrusion detection systems. The article considers general methods applicable to many di%erent types of networks, using speci'c algorithms as examples. The central theme is that latent variable hierarchical models constructed using Bayesian methods lead to coherent systems that can handle the complex distributions involved with ...

Network attached storage devices improve I/O performance by separating control and data paths and eliminating host intervention during data transfer. Devices are attached to a high speed network for data transfer and to a slower network for control messages. Hierarchical mass storage systems use disks to cache the most recently used les and tapes (robotic and manually mounted) to store the bulk...