A Quotient Space Formulation for Generative Statistical Analysis of Graphical Data

作者: Sudeep Sarkar , Xiaoyang Guo , Anuj Srivastava

DOI:

关键词:

摘要: … statistical analysis. Examples of graphical representations can be found in many areas, including social networks [57], gene expression networks [… in the Python implementation of FAQ …

参考文章(40)
M. Krcmar, A.P. Dhawan, Application of genetic algorithms in graph matching world congress on computational intelligence. ,vol. 6, pp. 3872- 3876 ,(1994) , 10.1109/ICNN.1994.374829
Brijnesh J. Jain, Klaus Obermayer, Learning in Riemannian Orbifolds arXiv: Learning. ,(2012)
Qiaozhu Mei, Meng Qu, Mingzhe Wang, Jian Tang, Ming Zhang, Jun Yan, LINE: Large-scale Information Network Embedding the web conference. pp. 1067- 1077 ,(2015) , 10.1145/2736277.2741093
Johan Ugander, Lars Backstrom, Cameron Marlow, Brian Karrer, The Anatomy of the Facebook Social Graph arXiv: Social and Information Networks. ,(2011)
Joshua T. Vogelstein, John M. Conroy, Vince Lyzinski, Louis J. Podrazik, Steven G. Kratzer, Eric T. Harley, Donniell E. Fishkind, R. Jacob Vogelstein, Carey E. Priebe, Fast Approximate Quadratic Programming for Graph Matching PLOS ONE. ,vol. 10, pp. e0121002- ,(2015) , 10.1371/JOURNAL.PONE.0121002
Pinar Yanardag, S.V.N. Vishwanathan, Deep Graph Kernels knowledge discovery and data mining. pp. 1365- 1374 ,(2015) , 10.1145/2783258.2783417
Facundo Mémoli, Gromov–Wasserstein Distances and the Metric Approach to Object Matching Foundations of Computational Mathematics. ,vol. 11, pp. 417- 487 ,(2011) , 10.1007/S10208-011-9093-5
William A. Mackaness, Kate M. Beard, Use of Graph Theory to Support Map Generalization Cartography and Geographic Information Systems. ,vol. 20, pp. 210- 221 ,(1993) , 10.1559/152304093782637479
Mark D.F. Shirley, Steve P. Rushton, The impacts of network topology on disease spread Ecological Complexity. ,vol. 2, pp. 287- 299 ,(2005) , 10.1016/J.ECOCOM.2005.04.005
Le Song, Kenji Fukumizu, Arthur Gretton, Kernel Embeddings of Conditional Distributions: A Unified Kernel Framework for Nonparametric Inference in Graphical Models IEEE Signal Processing Magazine. ,vol. 30, pp. 98- 111 ,(2013) , 10.1109/MSP.2013.2252713