ArticleComputer physics communications2019
Efficient sampling of spreading processes on complex networks using a composition and rejection algorithm.
Article in Computer physics communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Contagion-preserving compression for multiscale epidemic modeling.Science advances · 2026Article
- Efficient Gillespie algorithms for spreading phenomena in large and heterogeneous higher-order networks.Nature communications · 2026Article
- Unifying non-Markovian dynamics and agent heterogeneity in scalable stochastic networks.Nature communications · 2026Article
- Epydemix: An open-source Python package for epidemic modeling with integrated approximate Bayesian calibration.PLoS computational biology · 2025Article
- Stochastic diffusion using mean-field limits to approximate master equations.Royal Society open science · 2025Article
- Active querying approach to epidemic source detection on contact networks.Scientific reports · 2023Article
- Understanding the impact of digital contact tracing during the COVID-19 pandemic.PLOS digital health · 2022Article
- Effective resistance against pandemics: Mobility network sparsification for high-fidelity epidemic simulations.PLoS computational biology · 2022Article
- Reaction-diffusion models in weighted and directed connectomes.PLoS computational biology · 2022Article
- Article
- Social Confinement and Mesoscopic Localization of Epidemics on Networks.Physical review letters · 2021Article
- Outbreak detection for temporal contact data.Applied network science · 2021Article
- Article
- Immunization strategies in networks with missing data.PLoS computational biology · 2020Article
- Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Efficient stochastic simulation algorithms are of paramount importance to the study of spreading phenomena on complex networks. Using insights and analytical results from network science, we discuss how the structure of contacts affects the efficiency of current algorithms. We show that algorithms believed to require
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Registered trials
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