COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring. |

University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > Recognizing graphs formed by spatial random processes

## Recognizing graphs formed by spatial random processesAdd to your list(s) Download to your calendar using vCal - Jeanette Janssen (Dalhousie University)
- Monday 12 December 2016, 16:00-16:45
- Seminar Room 1, Newton Institute.
If you have a question about this talk, please contact info@newton.ac.uk. SNAW04 - Dynamic Networks In many real life applications, network formation can be modelled using a spatial random graph model: vertices are embedded in a metric space S, and pairs of vertices are more likely to be connected if they are closer together in the space. A general geometric graph model that captures this concept is G(n,w), where w is a symmetric “link probability” function from SxS to [0,1]. To guarantee the spatial nature of the random graph, we requite that this function has the property that, for fixed x in S, w(x,y) decreases as y is moved further away from x. The function w can be seen as the graph limit of the sequence G(n,w) as n goes to infinity. This talk is part of the Isaac Newton Institute Seminar Series series. ## This talk is included in these lists:- All CMS events
- Cambridge Big Data
- Featured lists
- INI info aggregator
- Isaac Newton Institute Seminar Series
- School of Physical Sciences
- Seminar Room 1, Newton Institute
- ndk22's list
- rp587
Note that ex-directory lists are not shown. |
## Other listsHistory and the Law 2030 vision for the Cambridge sub-region CTR Seminar Series## Other talksThe Exposome in Epidemiological Practice Regulatory principles in human development and evolution Inelastic neutron scattering and µSR investigations of an anisotropic hybridization gap in the Kondo insulators: CeT2Al10 (T=Fe, Ru and Os) Designing Active Macroscopic Heat Engines Making Refuge: Calais and Cambridge Universality in Active Matter |