igraph

igraph is a software package for complex network analysis and graph theory, with an emphasis on efficiency, portability and ease of use. igraph can be programmed in R, Python, Mathematica and C/C++.

Keywords for this software

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References in zbMATH (referenced in 209 articles )

Showing results 1 to 20 of 209.
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  1. Battaglini, M., Leone Sciabolazza, V., Patacchini, E., Peng, S: econet: An R Package for Parameter-Dependent Network Centrality Measures (2022) not zbMATH
  2. Etienne Côme, Nicolas Jouvin : greed: An R Package for Model-Based Clustering by Greedy Maximization of the Integrated Classification Likelihood (2022) arXiv
  3. Hernández, G.; Martín del Rey, A.: Community-distributed compartmental models (2022)
  4. Hu, Yaofang; Wang, Wanjie; Yu, Yi: Graph matching beyond perfectly-overlapping Erdős-Rényi random graphs (2022)
  5. Ikica, Barbara; Gabrovšek, Boštjan; Povh, Janez; Žerovnik, Janez: Clustering as a dual problem to colouring (2022)
  6. Jeffrey W. Hollister, Dorothy Q. Kellogg, Qian Lei-Parent, Emily Wilson, Cary Chadwick, David Dickson, Arthur Gold, Chester Arnold: nsink: An R package for flow path nitrogen removal estimation (2022) not zbMATH
  7. Kothiyal, Manuja; Kumar, Santosh; Sukumar, N.: Investigation of chemical space networks using graph measures and random matrix theory (2022)
  8. Marino, Maria Francesca; Pandolfi, Silvia: Hybrid maximum likelihood inference for stochastic block models (2022)
  9. Peeters, C. F. W., Bilgrau, A. E., van Wieringen, W. N. : rags2ridges: A One-Stop-l2-Shop for Graphical Modeling of High-Dimensional Precision Matrices (2022) not zbMATH
  10. Roy, Arkaprava; Ghosal, Subhashis: Optimal Bayesian smoothing of functional observations over a large graph (2022)
  11. Scutari, Marco; Denis, Jean-Baptiste: Bayesian networks. With examples in R (2022)
  12. Tavaré, Simon: A note on the screaming toes game (2022)
  13. Yin, Siyuan; Hu, Yanmei; Ren, Yuchun: The parallel computing of node centrality based on GPU (2022)
  14. Yu, Han; Hageman Blair, Rachael: Scalable module detection for attributed networks with applications to breast cancer (2022)
  15. Zhu, Kailun; Kurowicka, Dorota: Regular vines with strongly chordal pattern of (conditional) independence (2022)
  16. Antunes, Nelson; Bhamidi, Shankar; Guo, Tianjian; Pipiras, Vladas; Wang, Bang: Sampling based estimation of in-degree distribution for directed complex networks (2021)
  17. Arroyo, Jesús; Sussman, Daniel L.; Priebe, Carey E.; Lyzinski, Vince: Maximum likelihood estimation and graph matching in errorfully observed networks (2021)
  18. Arthur A. B. Pessa, Haroldo V. Ribeiro: ordpy: A Python package for data analysis with permutation entropy and ordinal network methods (2021) arXiv
  19. Artur Karczmarczyk, Jarosław Jankowski, Jarosław Wątróbski: OONIS - Object-Oriented Network Infection Simulator (2021) not zbMATH
  20. Austen Bernardi, Jessica M.J. Swanson: CycFlowDec: A Python module for decomposing flow networks using simple cycles (2021) not zbMATH

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