Error and attacktolerance of complex network s
By Paolo Crucitti, Vito Latora, Massimo Marchiori, Andrea Rapisarda. 2004
1,265 citations recorded by the source corpus.
Subfields: Global and Planetary Change, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/f7331752c2d0de039836dc6b7e24e4ca3bb45e7c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Global and Planetary Change
- Olaf Sporns
- Michael Breakspear
- Patric Hagmann
- Leila Cammoun
- John Foster
- Jordi Bascompte
- J. Olesen
- Colin Brown
In Statistical and Nonlinear Physics
- Márk Jelasity
- Olaf Sporns
- Wenxu Wang
- Palash Goyal
- Michael Breakspear
- Ying-Cheng Lai
- Anne-Marie Kermarrec
- Aram Galstyan
Citations in the corpus
- The ecological consequences of complex topology and nested structure in pollination webs. (2006, background): “It is interesting that, confirming expectations of models for abiotic networks (Albert and Barabasi 2002; Albert et al. 2000; Barabasi and Albert 1999; Barabasi et al. 2000; Jeong et al. 2000), KAT1, a scale-free network was less robust to the loss of plant species.”
- Modeling the Impact of Lesions in the Human Brain (2009, background): “The structural or functional robustness of networks has been investigated in a number of complex systems [12,13], including biological networks [14–16] In the case of the brain, acute injuries from trauma, tumor, or stroke, as well as chronic or degenerative disturbances due to disease, correspond t”
- Measuring resilience in energy systems: insights from a range of disciplines (2016, background): “Network theory suggests that networks that have redundant interconnections are more robust complex systems [79].”
- Exact controllability of complex networks (2013, background): “It can be verified that systems (equation (1)) and (equation (10)) have the same controllability in the sense that rank(lIN A, B)1⁄4 rank(lIN J, Q), with rank(B)1⁄4 rank(Q).”
- The Peer Sampling Service: Experimental Evaluation of Unstructured Gossip-Based Implementations (2004, background): “The motivation for looking at degree distribution is threefold and includes its direct relationship with reliability to different patterns of node failures [2], its crucial effect on the exact way epidemics are spread (and therefore on the way epidemic-based broadcasting is performed) [23] and final”
- Embedding Networks with Edge Attributes (2018, background): “Other types of network include author collaboration network [8], router network [3] and language networks [14].”