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On algebraic graph theory and the dynamics of innovation networks
1.  Chair of Systems Design, ETH Zürich, Kreuzplatz 5, CH8032 Zürich, Switzerland, Switzerland, Switzerland 
2.  Chair of Systems Design, ETH Zürich, Kreuzplatz 5, 8032 Zürich 
[1] 
Mirela Domijan, Markus Kirkilionis. Graph theory and qualitative analysis of reaction networks. Networks & Heterogeneous Media, 2008, 3 (2) : 295322. doi: 10.3934/nhm.2008.3.295 
[2] 
Konstantin Avrachenkov, Giovanni Neglia, Vikas Vikram Singh. Network formation games with teams. Journal of Dynamics & Games, 2016, 3 (4) : 303318. doi: 10.3934/jdg.2016016 
[3] 
Liu Hui, Lin Zhi, Waqas Ahmad. Network(graph) data research in the coordinate system. Mathematical Foundations of Computing, 2018, 1 (1) : 110. doi: 10.3934/mfc.2018001 
[4] 
Deena Schmidt, Janet Best, Mark S. Blumberg. Random graph and stochastic process contributions to network dynamics. Conference Publications, 2011, 2011 (Special) : 12791288. doi: 10.3934/proc.2011.2011.1279 
[5] 
Barton E. Lee. Consensus and voting on large graphs: An application of graph limit theory. Discrete & Continuous Dynamical Systems, 2018, 38 (4) : 17191744. doi: 10.3934/dcds.2018071 
[6] 
V. Lanza, D. Ambrosi, L. Preziosi. Exogenous control of vascular network formation in vitro: a mathematical model. Networks & Heterogeneous Media, 2006, 1 (4) : 621637. doi: 10.3934/nhm.2006.1.621 
[7] 
YaoLi Chuang, Tom Chou, Maria R. D'Orsogna. A network model of immigration: Enclave formation vs. cultural integration. Networks & Heterogeneous Media, 2019, 14 (1) : 5377. doi: 10.3934/nhm.2019004 
[8] 
Marco Scianna, Luca Munaron. Multiscale model of tumorderived capillarylike network formation. Networks & Heterogeneous Media, 2011, 6 (4) : 597624. doi: 10.3934/nhm.2011.6.597 
[9] 
Peter Hinow, Edward A. Rietman, Sara Ibrahim Omar, Jack A. Tuszyński. Algebraic and topological indices of molecular pathway networks in human cancers. Mathematical Biosciences & Engineering, 2015, 12 (6) : 12891302. doi: 10.3934/mbe.2015.12.1289 
[10] 
Yvjing Yang, Yang Liu, Jungang Lou, Zhen Wang. Observability of switched Boolean control networks using algebraic forms. Discrete & Continuous Dynamical Systems  S, 2021, 14 (4) : 15191533. doi: 10.3934/dcdss.2020373 
[11] 
Leon Petrosyan, David Yeung. Shapley value for differential network games: Theory and application. Journal of Dynamics & Games, 2021, 8 (2) : 151166. doi: 10.3934/jdg.2020021 
[12] 
Robert Carlson. Spectral theory for nonconservative transmission line networks. Networks & Heterogeneous Media, 2011, 6 (2) : 257277. doi: 10.3934/nhm.2011.6.257 
[13] 
Maya Mincheva, Gheorghe Craciun. Graphtheoretic conditions for zeroeigenvalue Turing instability in general chemical reaction networks. Mathematical Biosciences & Engineering, 2013, 10 (4) : 12071226. doi: 10.3934/mbe.2013.10.1207 
[14] 
A. C. Eberhard, JP. Crouzeix. Existence of closed graph, maximal, cyclic pseudomonotone relations and revealed preference theory. Journal of Industrial & Management Optimization, 2007, 3 (2) : 233255. doi: 10.3934/jimo.2007.3.233 
[15] 
Xianmin Geng, Shengli Zhou, Jiashan Tang, Cong Yang. A sufficient condition for classified networks to possess complex network features. Networks & Heterogeneous Media, 2012, 7 (1) : 5969. doi: 10.3934/nhm.2012.7.59 
[16] 
JianJun Xu, Junichiro Shimizu. Asymptotic theory for disclike crystal growth (II): interfacial instability and pattern formation at early stage of growth. Communications on Pure & Applied Analysis, 2004, 3 (3) : 527543. doi: 10.3934/cpaa.2004.3.527 
[17] 
Serap Ergün, Bariş Bülent Kırlar, Sırma Zeynep Alparslan Gök, GerhardWilhelm Weber. An application of crypto cloud computing in social networks by cooperative game theory. Journal of Industrial & Management Optimization, 2020, 16 (4) : 19271941. doi: 10.3934/jimo.2019036 
[18] 
Changyan Di, Qingguo Zhou, Jun Shen, Li Li, Rui Zhou, Jiayin Lin. Innovation event model for STEM education: A constructivism perspective. STEM Education, 2021, 1 (1) : 6074. doi: 10.3934/steme.2021005 
[19] 
Zhuwei Qin, Fuxun Yu, Chenchen Liu, Xiang Chen. How convolutional neural networks see the world  A survey of convolutional neural network visualization methods. Mathematical Foundations of Computing, 2018, 1 (2) : 149180. doi: 10.3934/mfc.2018008 
[20] 
D. Warren, K Najarian. Learning theory applied to Sigmoid network classification of protein biological function using primary protein structure. Conference Publications, 2003, 2003 (Special) : 898904. doi: 10.3934/proc.2003.2003.898 
2019 Impact Factor: 1.053
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