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Generating realistic scaled complex networks

Christian L. Staudt, Michael Hamann, Alexander Gutfraind, Ilya Safro, Henning Meyerhenke
2017 Applied Network Science  
We argue that ReCoN is a scalable and effective tool for modeling a given network while preserving important properties at both micro- and macroscopic scales, and for scaling the exemplar data by orders  ...  Research on generative models plays a central role in the emerging field of network science, studying how statistical patterns found in real networks could be generated by formal rules.  ...  A preliminary version of the paper was presented at the 5th International Workshop on Complex Networks and their Applications .  ... 
doi:10.1007/s41109-017-0054-z pmid:30533515 pmcid:PMC6225971 fatcat:2rdb2j6q4bgifepkgeoxz5dx2e

Generating realistic scaled complex networks [article]

Christian L. Staudt, Michael Hamann, Alexander Gutfraind, Ilya Safro,, Henning Meyerhenke
2017 arXiv   pre-print
We argue that ReCoN is a scalable and effective tool for modeling a given network while preserving important properties at both micro- and macroscopic scales, and for scaling the exemplar data by orders  ...  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.  ...  Outline and contribution In this paper we develop and evaluate a fast generator that focuses on creating realistic scaled replicas of complex networks.  ... 
arXiv:1609.02121v2 fatcat:zeecu4dr45bh5go24g5kjcojre

Relationship-Aware Spatial Perception Fusion for Realistic Scene Layout Generation [article]

Hongdong Zheng, Yalong Bai, Wei Zhang, Tao Mei
2019 arXiv   pre-print
The significant progress on Generative Adversarial Networks (GANs) have made it possible to generate surprisingly realistic images for single object based on natural language descriptions.  ...  By using these two modules, our proposed framework tends to generate more commonsense layout which is helpful for realistic image generation.  ...  However, these image generation methods are mainly focus on single objects generation under limited domains such as birds or flowers, generating realistic scenes from complex sentences depicting multiple  ... 
arXiv:1909.00640v2 fatcat:qhf2iqnjgjc6bfh7lu3fmh3ykq

Does scale exist? An epistemological scale continuum for complex human–environment systems

Steven M. Manson
2008 Geoforum  
Viewpoints and tensions among scale epistemologies also suggest several general principles for using scale eVectively in human-environment research.  ...  Scale pervades interdisciplinary research on human-environment systems that exhibit hallmarks of complexity such as path dependence, nonlinearity, and surprise.  ...  U N C O R R E C T E D P R O O F Complex constructionist scales Complex scale has several points of contact with constructionist and network scales.  ... 
doi:10.1016/j.geoforum.2006.09.010 fatcat:m7ygm2fkkra2zltv7lgnykoe6q

Ensemble neuronal responses in a large-scale realistic model of the cerebellar cortex

Sergio Solinas, Timoteo Colnaghi, Egidio D'Angelo
2013 BMC Neuroscience  
Realistic simulation of central networks remains a challenge due to the complexity of internal connectivity and cellular mechanisms involved.  ...  The model is built in NEURON-PYTHON and is fully scalable, thus allowing to simulate large-scale networks of arbitrary size.  ...  Realistic simulation of central networks remains a challenge due to the complexity of internal connectivity and cellular mechanisms involved.  ... 
doi:10.1186/1471-2202-14-s1-p82 pmcid:PMC3704696 fatcat:4buvyspac5d5flzuzvsm7sutcq

A Management Framework for Automating Network Experiments and User Behaviour Emulation on Large Scale Testbed Facilities [chapter]

Steven Latré, Filip De Turck, Dimitri Papadimitriou, Piet Demeester
2010 Lecture Notes in Computer Science  
Generic test environments such as Emulab allow to perform large scale tests on different network topologies.  ...  While these facilities offer a tool to easily configure the topology, setting up realistic network scenarios afterwards is a manual and time consuming task involving the configuration of dozens of servers  ...  However, before these network components can be deployed in real-life networks, they need to be thoroughly validated through realistic and large scale experiments.  ... 
doi:10.1007/978-3-642-17694-4_27 fatcat:5ixwpqhcpnapznqxrj2rrawojq

Reliability Modelling and Simulation of Complex Systems

Y. Lin, D. Li, R. Kang
2013 Chemical Engineering Transactions  
We will review the progress made by network science recently including latest formalism of interdependent network theory, which can be used to understand and study the reliability problem of complex system  ...  As the network science becomes available to model and study the complex system, its underlying concept of statistical physics is suitable to understand the complex system from the relationship between  ...  Due to the findings of scale-free network structure in many realistic engineering system including transportation system and Internet, the robustness properties of scale-free networks have been used to  ... 
doi:10.3303/cet1333079 doaj:0b59faf07c4c44cb82ad1596c339d006 fatcat:c5ywwo7vfncsdcatlrpoj3bli4

Toward a full-scale computational model of the rat dentate gyrus

Calvin J. Schneider, Marianne Bezaire, Ivan Soltesz
2012 Frontiers in Neural Circuits  
neural network models.  ...  Previously, we published a functional NEURON model of the rat dentate gyrus with over 50,000 biophysically realistic, multicompartmental neurons, but network simulations could only utilize a single processor  ...  Through the cooperation of two software tools, the complexity of the model can be increased with the generation of variable and realistic dendritic morphology for the sample case of granule cells.  ... 
doi:10.3389/fncir.2012.00083 pmid:23162433 pmcid:PMC3499761 fatcat:lsngyyse5rghrojyyisqpccz7u

Connectivity distribution and attack tolerance of general networks with both preferential and random attachments

Zonghua Liu, Ying-Cheng Lai, Nong Ye, Partha Dasgupta
2002 Physics Letters A  
A general class of growing networks is constructed with both preferential and random attachments, which includes random and scale-free networks as limiting cases when a physical parameter is tuned.  ...  Study of the effect of random failures and intentional attacks on the performance of network suggests that general networks which are neither completely random nor scale-free are desirable.  ...  Since the ground-breaking papers by Barabási and Albert on scale-free networks [1] and by Watts and Strogatz on small-world networks [2] , the interest on large, growing, and complex networks has soared  ... 
doi:10.1016/s0375-9601(02)01317-8 fatcat:z4stkd3k2jcxhpe5cahuzl3tau

Generating Scaled Replicas of Real-World Complex Networks [chapter]

Christian L. Staudt, Michael Hamann, Ilya Safro, Alexander Gutfraind, Henning Meyerhenke
2016 Studies in Computational Intelligence  
We recommend ReCoN as a general practical method for creating realistic test data for the engineering of computational methods on networks, verification, and simulation studies.  ...  Our design yields a scalable and effective tool for replicating a given network while preserving important properties at both microand macroscopic scales and (optionally) scaling the replica by orders  ...  The Generation Algorithm ReCoN We introduce ReCoN, a generator for replicating and scaling complex networks. Its input is a graph and a community structure on it.  ... 
doi:10.1007/978-3-319-50901-3_2 fatcat:v7nqxl4o55c6bifoxr2aa4hpzm

Livermore Computer Network Simulation Program

Peter Barnes, Jr., James Brase, Thomas Canales, Matthew Damante, Matthew Horsley, David Jefferson, Ron Soltz
2012 Proceedings of the Fifth International Conference on Simulation Tools and Techniques  
(10K node) and above scale; incorporate near-realtime updates from the real global Internet; and generate traffic from realistic traffic models matched to observed data.  ...  Damante (mdamante@llnl.gov), ABSTRACT The Livermore Lab has embarked on a multi-year effort to develop a large-scale realistic network simulation capability.  ...  We believe that quantifying errors in mapping, generating realistic traffic, and multi-scale network modeling are all new. There are a number of specific tasks required.  ... 
doi:10.4108/icst.simutools.2012.247748 dblp:conf/simutools/BarnesBCDHJS12 fatcat:wofyjhyy3jbjbd4n5m43hzwfom

Generating Synthetic Gene Regulatory Networks [chapter]

Ramesh Ram, Madhu Chetty
2008 Lecture Notes in Computer Science  
These artificial but realistic GRN networks provide a simulation environment similar to a real-life laboratory microarray experiment.  ...  In this paper, we present an approach for synthetically generating gene networks using causal relationships.  ...  Further, the generated synthetic network is made realistic by incorporating complex network characteristics such as transmission delays, biological and experimental noise.  ... 
doi:10.1007/978-3-540-88436-1_21 fatcat:attlzm6hdfahrfc7udgrhlltvy

Optimization of Cascade-Resilient Electrical Infrastructures and its Validation by Power Flow Modeling

Yiping Fang, Nicola Pedroni, Enrico Zio
2015 Risk Analysis  
For each generators-distributors connection pattern considered in the NSBDE search, a computationally-cheap, topological model of failure cascading in a complex network (named, the Motter-Lai (ML) model  ...  In this paper, we are primarily concerned with power transmission networks and we consider the problem of allocation of generation to distributors by rewiring links under the objectives of maximizing network  ...  the more realistic OPA fast-scale model.  ... 
doi:10.1111/risa.12396 pmid:25933109 fatcat:x2zowdp5dnbijda6s4cpwvo2kq

Aerial GANeration: Towards Realistic Data Augmentation Using Conditional GANs [chapter]

Stefan Milz, Tobias Rüdiger, Sebastian Süss
2019 Landolt-Börnstein - Group III Condensed Matter  
For this reason, we propose a method to generate multi-sensor data sets using realistic data augmentation based on conditional generative adversarial networks (cGAN). cGANs have shown impressive results  ...  Hence, there is no need for expensive and complex 3D engines.  ...  Due to the scale variance and the low input image size, we observed failure cases for more complex structures Fig.8 .  ... 
doi:10.1007/978-3-030-11012-3_5 fatcat:a24ijllkz5d3vihjfdvzjtwfw4

Computing Networks: A General Framework to Contrast Neural and Swarm Cognitions

Carlos Gershenson
2010 Paladyn: Journal of Behavioral Robotics  
AbstractThis paper presents the Computing Networks (CNs) framework. CNs are used to generalize neural and swarm architectures.  ...  Artificial neural networks, ant colony optimization, particle swarm optimization, and realistic biological models are used as examples of instantiations of CNs.  ...  Computing Networks: A General Descriptive Framework Many systems can be described as networks, i.e. nodes connected by edges [13, 14] .  ... 
doi:10.2478/s13230-010-0015-z fatcat:hlsfm4kwhnbmtgu555fex5cv2u
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