A fast algorithm to approximate the spectral density of locally tree-like networks with assortativity (2023)
- Authors:
- USP affiliated authors: FUJITA, ANDRÉ - IME ; GUZMÁN, GROVER ENRIQUE CASTRO - IME
- Unidade: IME
- DOI: 10.1093/comnet/cnad005
- Subjects: GRAFOS ALEATÓRIOS; TEORIA ESPECTRAL
- Language: Inglês
- Imprenta:
- Source:
- Título: Journal of Complex Networks
- ISSN: 2051-1329
- Volume/Número/Paginação/Ano: v. 11, n. 2, p. 1-15, 2023
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
GUZMAN, Grover Enrique Castro e FUJITA, André. A fast algorithm to approximate the spectral density of locally tree-like networks with assortativity. Journal of Complex Networks, v. 11, n. 2, p. 1-15, 2023Tradução . . Disponível em: https://doi.org/10.1093/comnet/cnad005. Acesso em: 13 fev. 2026. -
APA
Guzman, G. E. C., & Fujita, A. (2023). A fast algorithm to approximate the spectral density of locally tree-like networks with assortativity. Journal of Complex Networks, 11( 2), 1-15. doi:10.1093/comnet/cnad005 -
NLM
Guzman GEC, Fujita A. A fast algorithm to approximate the spectral density of locally tree-like networks with assortativity [Internet]. Journal of Complex Networks. 2023 ; 11( 2): 1-15.[citado 2026 fev. 13 ] Available from: https://doi.org/10.1093/comnet/cnad005 -
Vancouver
Guzman GEC, Fujita A. A fast algorithm to approximate the spectral density of locally tree-like networks with assortativity [Internet]. Journal of Complex Networks. 2023 ; 11( 2): 1-15.[citado 2026 fev. 13 ] Available from: https://doi.org/10.1093/comnet/cnad005 - Primitive, edge-short, isometric, and pantochordal cycles
- StatGraph: an R package for complex network statistical analyses based on spectrum
- Vertex-wise graph’s spectral density decomposition and its applications
- A fast parameter estimator for large complex networks
- Spectral densities approximations of incidence-based locally treelike hypergraph matrices via the cavity method
- Convolution-based linear discriminant analysis for functional data classification
- Efficient Laplacian spectral density computations for networks with arbitrary degree distributions
- Statistical methods for hypergraphs: a parameter estimator, a model selection, and a comparative test
- Cavity approach for the approximation of spectral density of graphs with heterogeneous structures
- Network analysis of neuropsychiatry disorders
Informações sobre o DOI: 10.1093/comnet/cnad005 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3139733.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
