Clustering of heterogeneous populations of networks

Jean-Gabriel Young, 2, ∗ Alec Kirkley, 4, ∗ and M. E. J. Newman 5 Department of Mathematics and Statistics, University of Vermont, Burlington VT, USA Vermont Complex Systems Center, University of Vermont, Burlington VT, USA Department of Physics, University of Michigan, Ann Arbor MI, USA School of Data Science, City University of Hong Kong, Hong Kong Center for the Study of Complex Systems, University of Michigan, Ann Arbor MI, USA (Dated: January 25, 2022)

[1]  Tiago P. Peixoto.  Reconstructing networks with unknown and heterogeneous errors , 2018, Physical Review X.

[2]  Mark E. J. Newman,et al.  Network structure from rich but noisy data , 2017, Nature Physics.

[3]  Carey E. Priebe,et al.  Joint Embedding of Graphs , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Elena Deych,et al.  Gibbs distribution for statistical analysis of graphical data with a sample application to fcMRI brain images , 2016, Statistics in medicine.

[5]  P. Wolfe,et al.  Modeling Network Populations via Graph Distances , 2019, Journal of the American Statistical Association.

[6]  Carey E. Priebe,et al.  Statistical Inference on Errorfully Observed Graphs , 2012, 1211.3601.

[7]  D. Lauffenburger,et al.  Network inference , 2005 .

[8]  Can M. Le,et al.  Estimating a network from multiple noisy realizations , 2017, ArXiv.

[9]  Daniel S. Margulies,et al.  Connectome Smoothing via Low-Rank Approximations , 2016, IEEE Transactions on Medical Imaging.

[10]  Carter T. Butts,et al.  Network inference, error, and informant (in)accuracy: a Bayesian approach , 2003, Soc. Networks.

[11]  Zhengwu Zhang,et al.  Common and individual structure of brain networks , 2017, The Annals of Applied Statistics.

[12]  Leto Peel,et al.  Detecting Change Points in the Large-Scale Structure of Evolving Networks , 2014, AAAI.

[13]  Tiago P. Peixoto.  Inferring the mesoscale structure of layered, edge-valued, and time-varying networks. , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  D. Witten,et al.  The Multiple Random Dot Product Graph Model , 2018, 1811.12172.

[15]  Stochastic Relaxation , 2014, Computer Vision, A Reference Guide.

[16]  Tiago P. Peixoto,et al.  Change points, memory and epidemic spreading in temporal networks , 2017, Scientific Reports.

[17]  Dane Taylor,et al.  Clustering Network Layers with the Strata Multilayer Stochastic Block Model , 2015, IEEE Transactions on Network Science and Engineering.

[18]  Simon Lunagomez,et al.  Bayesian model-based clustering for multiple network data , 2021 .

[19]  O. Sporns.  Networks of the Brain , 2010 .

[20]  David B. Dunson,et al.  Bayesian data analysis, third edition , 2013 .

[21]  George T. Cantwell,et al.  Robust Bayesian inference of network structure from unreliable data , 2021, J. Complex Networks.

[22]  M. M. Meyer,et al.  Statistical Analysis of Multiple Sociometric Relations. , 1985 .

[23]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  Jean-Gabriel Young,et al.  Reconstruction of plant–pollinator networks from observational data , 2019, Nature Communications.

[25]  P. Alam.  ‘L’ , 2021, Composites Engineering: An A–Z Guide.

[26]  Kathleen M. Carley,et al.  Metric inference for social networks , 1994 .

[27]  D. A. Kenny,et al.  The Social Relations Model , 1984 .

[28]  M. E. J. Newman,et al.  Estimating network structure from unreliable measurements , 2018, Physical Review E.

[29]  Danielle S Bassett,et al.  Understanding the Emergence of Neuropsychiatric Disorders With Network Neuroscience. , 2018, Biological psychiatry. Cognitive neuroscience and neuroimaging.

[30]  A. F. Smith,et al.  Statistical analysis of finite mixture distributions , 1986 .

[31]  Daniele Durante,et al.  Nonparametric Bayes Modeling of Populations of Networks , 2014, 1406.7851.

[32]  Stratis Ioannidis,et al.  A family of tractable graph metrics , 2019, Appl. Netw. Sci..

[33]  Alex Pentland,et al.  Reality mining: sensing complex social systems , 2006, Personal and Ubiquitous Computing.

[34]  Ciro Cattuto,et al.  High-Resolution Measurements of Face-to-Face Contact Patterns in a Primary School , 2011, PloS one.

[35]  Reconstruction of plant–pollinator networks from observational data , 2021, Nature communications.

[36]  Michael C. Hout,et al.  Multidimensional Scaling , 2003, Encyclopedic Dictionary of Archaeology.

[37]  P. Deb.  Finite Mixture Models , 2008 .

[38]  Ernst Wit,et al.  Model-based clustering for populations of networks , 2018, Statistical Modelling.

[39]  C. Butts,et al.  Finite Mixtures of ERGMs for Ensembles of Networks , 2019 .

[40]  O. Sporns,et al.  Network neuroscience , 2017, Nature Neuroscience.

[41]  M. Meilă.  Comparing clusterings---an information based distance , 2007 .

[42]  Radford M. Neal.  Markov Chain Sampling Methods for Dirichlet Process Mixture Models , 2000 .

[43]  Carey E. Priebe,et al.  Inference for Multiple Heterogeneous Networks with a Common Invariant Subspace , 2019, J. Mach. Learn. Res..

[44]  David Lazer,et al.  Inferring friendship network structure by using mobile phone data , 2009, Proceedings of the National Academy of Sciences.

[45]  Eric D. Kolaczyk,et al.  Network Recovery from Unlabeled Noisy Samples , 2021 .