Preprints

  • Reconstruction of plant–pollinator networks from observational data
    J.-G. Young, F. S. Valdovinos, and M. E. J. Newman
    bioRxiv.org | Software

  • Recovering the past states of growing trees
    G. T. Cantwell, G. St-Onge, and J.-G. Young
    arXiv.org | Software

  • Changes in group size during resource shifts reveal drivers of sociality across the tree of life
    A. B. Kao, A. K. Hund, F. P. Santos, J.-G. Young, D. Bhat, J. Garland, R. A. Oomen, and H. F. McCreery
    bioRxiv.org

  • A clarified typology of core-periphery structure in networks
    R. J. Gallagher, J.-G. Young, and B. Foucault Welles
    arXiv.org | Software

  • Countering hate on social media: Large scale classification of hate and counter speech
    J. Garland, K. Ghazi-Zahedi, J.-G. Young, L. Hébert-Dufresne, and M. Galesic
    arXiv.org

  • Robust Bayesian inference of network structure from unreliable data
    J.-G. Young, G. T. Cantwell, and M. E. J. Newman
    arXiv.org | Software

  • Hypergraph reconstruction from network data
    J.-G. Young, G. Petri, and T. P. Peixoto
    arXiv.org | Software

  • Impact and dynamics of hate and counter speech online
    J. Garland, K. Ghazi-Zahedi, J.-G. Young, L. Hébert-Dufresne, and M. Galesic
    arXiv.org

Peer-Reviewed Journals

(listed in inverse chronological order)

  • Networks beyond pairwise interactions: structure and dynamics
    F. Battiston, G. Cencetti, I. Iacopini, V. Latora, M. Lucas, A. Patania, J.-G. Young, and G. Petri
    Phys. Rep. 874 (2020)
    arXiv.org | Journal

  • Improved mutual information measure for classification and community detection
    M. E. J. Newman, G. T. Cantwell, and J.-G. Young
    Phys. Rev. E, 101, 042304 (2020)
    arXiv.org | Journal

  • Macroscopic patterns of interacting contagions are indistinguishable from social reinforcement
    L. Hébert-Dufresne, S. V. Scarpino, and J.-G. Young
    Nature Physics (2020)
    arXiv.org | Journal | Supplementary Information | “News and views” by Sune Lehmann | PDF | Software | Slides

  • Phase transition in the recoverability of network history
    J.-G. Young, G. St-Onge, E. Laurence, C. Murphy, L. Hébert-Dufresne, and P. Desrosiers
    Phys. Rev. X, 9, 041056 (2019)
    arXiv.org | Journal | Supplementary Information | Software | Slides

  • Efficient sampling of spreading processes on complex networks using a composition and rejection algorithm
    G. St-Onge, J.-G. Young, L. Hébert-Dufresne, and L. J. Dubé
    Computer Physics Communications, 240, 30 (2019)
    arXiv.org | Journal | Software

  • Universality of the stochastic block model
    J.-G. Young, G. St-Onge, P. Desrosiers, and L. J. Dubé
    Phys. Rev. E, 98, 032309 (2018)
    arXiv.org | Journal | Slides

  • Exact analytical solution of irreversible binary dynamics on networks
    E. Laurence, J.-G. Young, S. Melnik, and L. J. Dubé
    Phys. Rev. E, 97, 032302 (2018)
    arXiv.org | Journal | Software

  • Phase transition of the susceptible-infected-susceptible dynamics on time-varying configuration model networks
    G. St-Onge, J.-G. Young, E. Laurence, C. Murphy, and L. J. Dubé
    Phys. Rev. E, 97, 022305 (2018)
    arXiv.org | Journal | Short note

  • Construction of and efficient sampling from the simplicial configuration model
    J.-G. Young, G. Petri, F. Vaccarino, and A. Patania
    Phys. Rev. E, 96, 032312 (2017)
    arXiv.org | Journal | Slides | Software

  • Strategic tradeoffs in competitor dynamics on adaptive networks
    L. Hébert-Dufresne, A. Allard, P.-A. Noël, J.-G. Young, and E. Libby
    Sci. Rep., 7, 7576 (2017)
    arXiv.org | Journal

  • Finite size analysis of the detectability limit of the stochastic block model
    J.-G. Young, P. Desrosiers, L. Hébert-Dufresne, E. Laurence, and L. J. Dubé
    Phys. Rev. E 95, 062304 (2017)
    arXiv.org | Journal | Software

  • Growing networks of overlapping communities with internal structure
    J.-G. Young, L. Hébert-Dufresne, A. Allard, and L. J. Dubé
    Phys. Rev. E 94, 022317 (2016)
    arXiv.org | Journal | Slides | Software

  • Constrained growth of complex scale-independent systems
    L. Hébert-Dufresne, A. Allard, J.-G. Young, and L. J. Dubé
    Phys. Rev. E 93, 032304 (2016)
    Editors’ Suggestion
    arXiv.org | Journal

  • Complex networks as an emerging property of hierarchical preferential attachment
    L. Hébert-Dufresne, E. Laurence, A. Allard, J.-G. Young, and L. J. Dubé
    Phys. Rev. E, 92, 062809 (2015)
    arXiv.org | Journal | Poster | Software

  • General and exact approach to percolation on random graphs
    A. Allard, L. Hébert-Dufresne, J.-G. Young, and L. J. Dubé
    Phys. Rev. E, 92, 062807 (2015)
    arXiv.org | Journal

  • A shadowing problem in the detection of overlapping communities:
    lifting the resolution limit through a cascading procedure

    J.-G. Young, A. Allard, L. Hébert-Dufresne, and L. J. Dubé
    PLoS ONE 10, e0140133 (2015)
    arXiv.org | Journal | Software

  • Coexistence of phases and the observability of random graphs
    A. Allard, L. Hébert-Dufresne, J.-G. Young, and L. J. Dubé
    Phys. Rev. E, 89, 022801 (2014)
    Editors’ Suggestion
    arXiv.org | Journal

  • Percolation on random networks with arbitrary k-core structure
    L. Hébert-Dufresne, A. Allard, J.-G. Young, and L. J. Dubé
    Phys. Rev. E, 88, 062820 (2013)
    arXiv.org | Journal

  • Global efficiency of local immunization on complex networks
    L. Hébert-Dufresne, A. Allard, J.-G. Young, and L. J. Dubé
    Sci. Rep., 3, 2171 (2013)
    arXiv.org | Journal

Conference Proceedings

  • Connected graphs with a given degree sequence: efficient sampling, correlations, community detection and robustness
    J. H. Ring IV, J.-G. Young and Laurent Hébert-Dufresne
    Proceedings of NetSci-X 2020
    PDF | Journal

Theses

  • Inférence et réseaux complexes (french)
    (Inference and complex networks)
    Ph.D. Thesis, Université Laval (2018)
    Corpus | PDF

  • De la détection de la structure communautaire des réseaux complexes (french)
    (Of community structure detection on complex networks)
    M.Sc. Thesis, Université Laval (2014)
    Corpus | PDF