Zobrazeno 1 - 10
of 160
pro vyhledávání: '"Staudt, Christian"'
Autor:
Staudt, Christian L., Hamann, Michael, Gutfraind, Alexander, Safro, Ilya, Meyerhenke, Henning
Research on generative models is a central project in the emerging field of network science, and it studies how statistical patterns found in real networks could be generated by formal rules. Output from these generative models is then the basis for
Externí odkaz:
http://arxiv.org/abs/1609.02121
Complex networks are relational data sets commonly represented as graphs. The analysis of their intricate structure is relevant to many areas of science and commerce, and data sets may reach sizes that require distributed storage and processing. We d
Externí odkaz:
http://arxiv.org/abs/1601.00289
Sparsification reduces the size of networks while preserving structural and statistical properties of interest. Various sparsifying algorithms have been proposed in different contexts. We contribute the first systematic conceptual and experimental co
Externí odkaz:
http://arxiv.org/abs/1601.00286
Sparsification reduces the size of networks while preserving structural and statistical properties of interest. Various sparsifying algorithms have been proposed in different contexts. We contribute the first systematic conceptual and experimental co
Externí odkaz:
http://arxiv.org/abs/1505.00564
Complex networks have become increasingly popular for modeling various real-world phenomena. Realistic generative network models are important in this context as they avoid privacy concerns of real data and simplify complex network research regarding
Externí odkaz:
http://arxiv.org/abs/1501.03545
Betweenness centrality ranks the importance of nodes by their participation in all shortest paths of the network. Therefore computing exact betweenness values is impractical in large networks. For static networks, approximation based on randomly samp
Externí odkaz:
http://arxiv.org/abs/1409.6241
We introduce NetworKit, an open-source software package for analyzing the structure of large complex networks. Appropriate algorithmic solutions are required to handle increasingly common large graph data sets containing up to billions of connections
Externí odkaz:
http://arxiv.org/abs/1403.3005
Collaboration networks arise when we map the connections between scientists which are formed through joint publications. These networks thus display the social structure of academia, and also allow conclusions about the structure of scientific knowle
Externí odkaz:
http://arxiv.org/abs/1306.5268
The amount of graph-structured data has recently experienced an enormous growth in many applications. To transform such data into useful information, fast analytics algorithms and software tools are necessary. One common graph analytics kernel is dis
Externí odkaz:
http://arxiv.org/abs/1304.4453
Publikováno v:
Nucl.Phys. B873 (2013) 343-371
In a class of supersymmetric flavor models predictions are based on residual symmetries of some subsectors of the theory such as those of the charged leptons and neutrinos. However, the vacuum expectation values of the so-called flavon fields general
Externí odkaz:
http://arxiv.org/abs/1302.5576