Unbiased sampling of network ensembles

Understand

Sampling random graphs with given properties is a key step in the analysis of networks, as random ensembles represent basic null models required to identify patterns such as communities and motifs.

• An important requirement is that the sampling process is unbiased and efficient.
• The main approaches are microcanonical, i.e.
• they sample graphs that match the enforced constraints exactly.