938 citations · 4.4k across the 50 of their papers we have counts for
18 papers · 1 filter
Statistical inference of dynamical processes on networks
Javier Ureña-Carrion, Tiago P. Peixoto, Gerardo Iñiguez
Mechanisms of interaction in spreading models are central to our quantitative understanding of networked contagion processes, from disease transmission to opinion dynamics. Yet, wh…
Systematic assessment of the quality of fit of the stochastic block model for empirical networks
Felipe Vaca-Ramírez, Tiago P. Peixoto
We perform a systematic analysis of the quality of fit of the stochastic block model (SBM) for 275 empirical networks spanning a wide range of domains and orders of size magnitude.…
Descriptive vs. inferential community detection in networks: pitfalls, myths, and half-truths
Tiago P. Peixoto
Community detection is one of the most important methodological fields of network science, and one which has attracted a significant amount of attention over the past decades. This…
The physics of higher-order interactions in complex systems
Federico Battiston, Enrico Amico, Alain Barrat +11
Complex networks have become the main paradigm for modelling the dynamics of interacting systems. However, networks are intrinsically limited to describing pairwise interactions, w…
Statistical inference of assortative community structures
Lizhi Zhang, Tiago P. Peixoto
We develop a principled methodology to infer assortative communities in networks based on a nonparametric Bayesian formulation of the planted partition model. We show that this app…
Null models for multi-optimized large-scale network structures
Sebastian Morel-Balbi, Tiago P. Peixoto
We study the emerging large-scale structures in networks subject to selective pressures that simultaneously drive towards higher modularity and robustness against random failures.…
Revealing consensus and dissensus between network partitions
Tiago P. Peixoto
Community detection methods attempt to divide a network into groups of nodes that share similar properties, thus revealing its large-scale structure. A major challenge when employi…
Merge-split Markov chain Monte Carlo for community detection
Tiago P. Peixoto
We present a Markov chain Monte Carlo scheme based on merges and splits of groups that is capable of efficiently sampling from the posterior distribution of network partitions, def…
Latent Poisson models for networks with heterogeneous density
Tiago P. Peixoto
Empirical networks are often globally sparse, with a small average number of connections per node, when compared to the total size of the network. However, this sparsity tends not…
Network reconstruction and community detection from dynamics
Tiago P. Peixoto
We present a scalable nonparametric Bayesian method to perform network reconstruction from observed functional behavior that at the same time infers the communities present in the…
Change points, memory and epidemic spreading in temporal networks
Tiago P. Peixoto, Laetitia Gauvin
Dynamic networks exhibit temporal patterns that vary across different time scales, all of which can potentially affect processes that take place on the network. However, most data-…
Network structure, metadata and the prediction of missing nodes and annotations
Darko Hric, Tiago P. Peixoto, Santo Fortunato
The empirical validation of community detection methods is often based on available annotations on the nodes that serve as putative indicators of the large-scale network structure.…
Disease Localization in Multilayer Networks
Guilherme Ferraz de Arruda, Emanuele Cozzo, Tiago P. Peixoto +2
We present a continuous formulation of epidemic spreading on multilayer networks using a tensorial representation, extending the models of monoplex networks to this context. We der…
Sampling motif-constrained ensembles of networks
Rico Fischer, Jorge C. Leitao, Tiago P. Peixoto +1
The statistical significance of network properties is conditioned on null models which satisfy spec- ified properties but that are otherwise random. Exponential random graph models…
Inferring the mesoscale structure of layered, edge-valued and time-varying networks
Tiago P. Peixoto
Many network systems are composed of interdependent but distinct types of interactions, which cannot be fully understood in isolation. These different types of interactions are oft…
Spontaneous centralization of control in a network of company ownerships
Sebastian M. Krause, Tiago P. Peixoto, Stefan Bornholdt
We introduce a model for the adaptive evolution of a network of company ownerships. In a recent work it has been shown that the empirical global network of corporate control is mar…
Evolution of robust network topologies: Emergence of central backbones
Tiago P. Peixoto, Stefan Bornholdt
We model the robustness against random failure or intentional attack of networks with arbitrary large-scale structure. We construct a block-based model which incorporates --- in a…
Trust transitivity in social networks
Oliver Richters, Tiago P. Peixoto
Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the…