Bob


Department of Network and Data Science
Central European University
Quellenstraße 51-55
1100 Vienna
Austria

A305

tiago@skewed.de
peixotot@ceu.edu
(Have a question about graph-tool? Please send a message to the mailing list, or open an issue.)

Curriculum Vitae

PGP key: 98507F25
My key has changed some time ago.

@tiago@social.skewed.de

@tiagopeixoto

gitlab

google scholar

ORCID

ResearcherID

Publons

[FSF Associate Member]

Tiago de Paula Peixoto

Scientific interests
Networks & Complex Systems
Statistical Physics & Applied Mathematics
Current position
Central European University — Associate Professor
Software projects
graph-tool — An efficient python module for manipulation and statistical analysis of graphs.

Research

My research focuses on characterizing, identifying and explaining large-scale patterns found in the structure and function of complex network systems — representing diverse phenomena with physical, biological, technological, or social origins — using principled approaches from statistical physics, nonlinear dynamics and Bayesian inference.

(If you are interested in inferring modular structures in networks using graph-tool, take a look at this HOWTO.)

Open positions

Interested PhD candidates are encouraged to apply for the "PhD Program in Network Science at CEU".

Publications

Pre-prints

  1. Disentangling homophily, community structure and triadic closure in networks
    Tiago P. Peixoto
    arXiv: 2101.02510
    Code is available. See the HOWTO.
  2. Hypergraph reconstruction from network data
    Jean-Gabriel Young, Giovanni Petri, Tiago P. Peixoto
    arXiv: 2008.04948

Journal papers

  1. Revealing consensus and dissensus between network partitions
    Tiago P. Peixoto
    Phys. Rev. X 11 021003 (2021)
    DOI: 10.1103/PhysRevX.11.021003 [sci-hub, @tor]
    arXiv: 2005.13977
    Code is available. See the HOWTO.
  2. Statistical inference of assortative community structures
    Lizhi Zhang, Tiago P. Peixoto
    Phys. Rev. Research 2 043271 (2020)
    DOI: 10.1103/PhysRevResearch.2.043271 [sci-hub, @tor]
    arXiv: 2006.14493
    Code is available. See the HOWTO.
  3. Merge-split Markov chain Monte Carlo for community detection
    Tiago P. Peixoto
    Phys. Rev. E 102 012305 (2020)
    DOI: 10.1103/PhysRevE.102.012305 [sci-hub, @tor]
    arXiv: 2003.07070
    Code is available. See the HOWTO.
  4. Latent Poisson models for networks with heterogeneous density
    Tiago P. Peixoto
    Phys. Rev. E 102 012309 (2020)
    DOI: 10.1103/PhysRevE.102.012309 [sci-hub, @tor]
    arXiv: 2002.07803
    Code is available. See the HOWTO.
  5. Null models for multi-optimized large-scale network structures
    Sebastian Morel-Balbi, Tiago P. Peixoto
    Phys. Rev. E 102 032306 (2020)
    DOI: 10.1103/PhysRevE.102.032306 [sci-hub, @tor]
    arXiv: 2006.08508
  6. Network reconstruction and community detection from dynamics
    Tiago P. Peixoto
    Phys. Rev. Lett. 123 128301 (2019)
    DOI: 10.1103/PhysRevLett.123.128301 [sci-hub, @tor]
    arXiv: 1903.10833
    Code is available. See the HOWTO.
  7. Reconstructing networks with unknown and heterogeneous errors
    Tiago P. Peixoto
    Phys. Rev. X 8 041011 (2018)
    DOI: 10.1103/PhysRevX.8.041011 [sci-hub, @tor]
    arXiv: 1806.07956
    Code is available. See the HOWTO.
  8. A network approach to topic models
    Martin Gerlach, Tiago P. Peixoto, Eduardo G. Altmann
    Science Advances 4 eaaq1360 (2018)
    DOI: 10.1126/sciadv.aaq1360 [sci-hub, @tor]
    arXiv: 1708.01677
    Code is available. See also the network inference HOWTO.
  9. Nonparametric weighted stochastic block models
    Tiago P. Peixoto
    Phys. Rev. E 97 012306 (2018)
    DOI: 10.1103/PhysRevE.97.012306 [sci-hub, @tor]
    arXiv: 1708.01432
    Code is available. See the HOWTO.
  10. Change points, memory and epidemic spreading in temporal networks
    Tiago P. Peixoto, Laetitia Gauvin
    Sci. Rep. 8 15511 (2018)
    DOI: 10.1038/s41598-018-33313-1 [sci-hub, @tor]
    arXiv: 1712.08948
  11. Consistencies and inconsistencies between model selection and link prediction in networks
    Toni Vallès-Català, Tiago P. Peixoto, Roger Guimerà, Marta Sales-Pardo
    Phys. Rev. E 97 062316 (2018)
    DOI: 10.1103/PhysRevE.97.062316 [sci-hub, @tor]
    arXiv: 1705.07967
    Code is available. See the HOWTO.
  12. Modeling sequences and temporal networks with dynamic community structures
    Tiago P. Peixoto, Martin Rosvall
    Nature Communications 8, 582 (2017)
    DOI: 10.1038/s41467-017-00148-9 [sci-hub, @tor]
    arXiv: 1509.04740
  13. Nonparametric Bayesian inference of the microcanonical stochastic block model
    Tiago P. Peixoto
    Phys. Rev. E 95 012317 (2017)
    DOI: 10.1103/PhysRevE.95.012317 [sci-hub, @tor]
    arXiv: 1610.02703
    Code is available. See the HOWTO.
  14. Disease localization in multilayer networks
    Guilherme Ferraz de Arruda, Emanuele Cozzo, Tiago P. Peixoto, Francisco A. Rodrigues, Yamir Moreno
    Phys. Rev. X 7 1 011014 (2017)
    DOI: 10.1103/PhysRevX.7.011014 [sci-hub, @tor]
    arXiv: 1509.07054
  15. Network structure, metadata, and the prediction of missing nodes and annotations
    Darko Hric, Tiago P. Peixoto, Santo Fortunato
    Phys. Rev. X 6 3 031038 (2016)
    DOI: 10.1103/PhysRevX.6.031038 [sci-hub, @tor]
    arXiv: 1604.00255
  16. Generalized communities in networks
    M. E. J. Newman, Tiago P. Peixoto
    Phys. Rev. Lett. 115, 088701 (2015)
    DOI: 10.1103/PhysRevLett.115.088701 [sci-hub, @tor]
    arXiv: 1505.07478
    Cover of the PRL issue!
  17. Sampling motif-constrained ensembles of networks
    Rico Fisher, Jorge C. Leitão, Tiago P. Peixoto, Eduardo G. Altmann
    Phys. Rev. Lett. 115, 188701 (2015)
    DOI: 10.1103/PhysRevLett.115.188701 [sci-hub, @tor]
    arXiv: 1507.08696
  18. Inferring the mesoscale structure of layered, edge-valued and time-varying networks
    Tiago P. Peixoto
    Phys. Rev. E 92, 042807 (2015)
    DOI: 10.1103/PhysRevE.92.042807 [sci-hub, @tor]
    arXiv: 1504.02381
    Code is available. See the HOWTO.
  19. Model selection and hypothesis testing for large-scale network models with overlapping groups
    Tiago P. Peixoto
    Phys. Rev. X 5, 011033 (2015)
    DOI: 10.1103/PhysRevX.5.011033 [sci-hub, @tor]
    arXiv: 1409.3059
    Code is available. See the HOWTO.
  20. Maximum-entropy large-scale structures of Boolean networks optimized for criticality
    Marco Möller, Tiago P. Peixoto
    New J. Phys. 17 043021 (2015)
    DOI: 10.1088/1367-2630/17/4/043021 [sci-hub, @tor]
  21. Limits and Trade-Offs of Topological Network Robustness
    Christopher Priester, Sebastian Schmitt, Tiago P. Peixoto
    PLoS ONE 9(9): e108215 (2014)
    DOI: 10.1371/journal.pone.0108215 [sci-hub, @tor]
  22. Hierarchical block structures and high-resolution model selection in large networks
    Tiago P. Peixoto
    Phys. Rev. X 4, 011047 (2014)
    DOI: 10.1103/PhysRevX.4.011047 [sci-hub, @tor]
    arXiv: 1310.4377
    Code is available. See the HOWTO.
  23. Efficient Monte Carlo and greedy heuristic for the inference of stochastic block models
    Tiago P. Peixoto
    Phys. Rev. E 89, 012804 (2014)
    DOI: 10.1103/PhysRevE.89.012804 [sci-hub, @tor]
    arXiv: 1310.4378
    Code is available. See the HOWTO.
  24. Eigenvalue Spectra of Modular Networks
    Tiago P. Peixoto
    Phys. Rev. Lett. 111 9 098701 (2013)
    DOI: 10.1103/PhysRevLett.111.098701 [sci-hub, @tor]
    arXiv: 1306.2507
  25. Spontaneous centralization of control in a network of company ownerships
    Sebastian M. Krause, Tiago P. Peixoto, Stefan Bornholdt
    PLoS ONE 8(12): e80303 (2013)
    DOI: 10.1371/journal.pone.0080303 [sci-hub, @tor]
    arXiv: 1306.3422
  26. Parsimonious Module Inference in Large Networks
    Tiago P. Peixoto
    Phys. Rev. Lett. 110 148701 (2013)
    DOI: 10.1103/PhysRevLett.110.148701 [sci-hub, @tor]
    arXiv: 1212.4794
    Code is available. See the HOWTO.
  27. Evolution of Robust Network Topologies: Emergence of Central Backbones
    Tiago P. Peixoto, Stefan Bornholdt
    Phys. Rev. Lett. 109 11 118703 (2012)
    DOI: 10.1103/PhysRevLett.109.118703 [sci-hub, @tor]
    arXiv: 1205.2909
    Coverage: Synopsis in Physics
  28. Entropy of stochastic blockmodel ensembles
    Tiago P. Peixoto
    Phys. Rev. E 85 5 056122 (2012)
    DOI: 10.1103/PhysRevE.85.056122 [sci-hub, @tor]
    arXiv: 1112.6028
  29. No Need for Conspiracy: Self-Organized Cartel Formation in a Modified Trust Game
    Tiago P. Peixoto, Stefan Bornholdt
    Phys. Rev. Lett. 108 21 218702 (2012)
    DOI: 10.1103/PhysRevLett.108.218702 [sci-hub, @tor]
    arXiv: 1201.3798
    Coverage: (Phys.org) High gas prices may be explained by self-organized cartel behavior, (Physics arXiv Blog) Cartels Are an Emergent Phenomenon, Say Complexity Theorists, (Jura Forum) Bremer Uni-Studie: Flächendeckend höhere Benzinpreise deuten nicht gleich auf Preisabsprachen hin, (kreiszeitung.de) Benzinpreis: Kein Hinweis auf Absprache
  30. Emergence of robustness against noise: A structural phase transition in evolved models of gene regulatory networks
    Tiago P. Peixoto
    Phys. Rev. E 85 4 041908 (2012)
    DOI: 10.1103/PhysRevE.85.041908 [sci-hub, @tor]
    arXiv: 1108.4341
  31. Reliable dynamics in Boolean and continuous networks
    Eva Ackermann, Tiago P. Peixoto, Barbara Drossel
    New J. Phys. 14 12 123029 (2012)
    DOI: 10.1088/1367-2630/14/12/123029 [sci-hub, @tor]
  32. The behavior of noise-resilient Boolean networks with diverse topologies
    Tiago P Peixoto
    J. Stat. Mech. 2012 01 P01006 (2012)
    DOI: 10.1088/1742-5468/2012/01/P01006 [sci-hub, @tor]
    arXiv: 1108.4329
  33. Trust Transitivity in Social Networks
    Oliver Richters, Tiago P. Peixoto
    PLOS ONE 6 4 e18384 (2011)
    DOI: 10.1371/journal.pone.0018384 [sci-hub, @tor]
    arXiv: 1012.1358
  34. Density profile and polymer configurations for a polymer melt in a regular array of nanotubes
    Tiago P Peixoto, Barbara Drossel
    New J. Phys. 13 7 073030 (2011)
    DOI: 10.1088/1367-2630/13/7/073030 [sci-hub, @tor]
  35. The phase diagram of random Boolean networks with nested canalizing functions
    T. P. Peixoto
    Eur. Phys. J. B 78 2 187--192 (2010)
    DOI: 10.1140/epjb/e2010-10559-0 [sci-hub, @tor]
    arXiv: 1007.3411
  36. Boolean networks with robust and reliable trajectories
    Christoph Schmal, Tiago P Peixoto, Barbara Drossel
    New J. Phys. 12 11 113054 (2010)
    DOI: 10.1088/1367-2630/12/11/113054 [sci-hub, @tor]
    arXiv: 1008.1726
  37. Redundancy and Error Resilience in Boolean Networks
    Tiago P. Peixoto
    Phys. Rev. Lett. 104 4 048701 (2010)
    DOI: 10.1103/PhysRevLett.104.048701 [sci-hub, @tor]
    arXiv: 0909.1740
  38. Spatiotemporal correlations of aftershock sequences
    Tiago P. Peixoto, Katharina Doblhoff-Dier, Jörn Davidsen
    J. Geophys. Res. 115 B10309 (2010)
    DOI: 201010.1029/2010JB007626 [sci-hub, @tor]
  39. Polymer confinement effects in aligned carbon nanotubes arrays
    Pitamber Mahanandia, Jörg J. Schneider, Marina Khaneft, Bernd Stühn, Tiago P. Peixoto, Barbara Drossel
    Phys. Chem. Chem. Phys. 12 17 4407 (2010)
    DOI: 10.1039/b922906j [sci-hub, @tor]
  40. Boolean networks with reliable dynamics
    Tiago P. Peixoto, Barbara Drossel
    Phys. Rev. E 80 5 056102 (2009)
    DOI: 10.1103/PhysRevE.80.056102 [sci-hub, @tor]
    arXiv: 0905.0925
  41. Noise in random Boolean networks
    Tiago P. Peixoto, Barbara Drossel
    Phys. Rev. E 79 3 036108 (2009)
    DOI: 10.1103/PhysRevE.79.036108 [sci-hub, @tor]
    arXiv: 0808.3087
  42. Network of recurrent events for the Olami-Feder-Christensen model
    Tiago P. Peixoto, Jörn Davidsen
    Phys. Rev. E 77 6 066107 (2008)
    DOI: 10.1103/PhysRevE.77.066107 [sci-hub, @tor]
    arXiv: 0803.1404
  43. Network of epicenters of the Olami-Feder-Christensen model of earthquakes
    Tiago P. Peixoto, Carmen P. C. Prado
    Phys. Rev. E 74 1 016126 (2006)
    DOI: 10.1103/PhysRevE.74.016126 [sci-hub, @tor]
    arXiv: cond-mat/0602244
  44. Statistics of epicenters in the Olami-Feder-Christensen model in two and three dimensions
    Tiago P. Peixoto, Carmen P. C. Prado
    Physica A 342 1-2 171--177 (2004)
    DOI: 10.1016/j.physa.2004.04.075 [sci-hub, @tor]
  45. Distribution of epicenters in the Olami-Feder-Christensen model
    Tiago P. Peixoto, Carmen P. C. Prado
    Phys. Rev. E 69 2 025101 (2004)
    DOI: 10.1103/PhysRevE.69.025101 [sci-hub, @tor]
    arXiv: cond-mat/0310366

Book chapters

  1. Bayesian stochastic blockmodeling
    Tiago P. Peixoto
    Chapter in “Advances in Network Clustering and Blockmodeling,” edited by P. Doreian, V. Batagelj, A. Ferligoj (Wiley, 2019)
    DOI: 10.1002/9781119483298.ch11 [sci-hub, @tor]
    arXiv: 1705.10225
    Code is available. See the HOWTO.
  2. Modelling Temporal Networks with Markov Chains, Community Structures and Change Points
    Tiago P. Peixoto, Martin Rosvall
    Chapter in “Temporal Network Theory,” edited by Holme P., Saramäki J. (Springer, 2019)
    DOI: 10.1007/978-3-030-23495-9_4 [sci-hub, @tor]
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