SBM Background $$k=[1,10], p_i=[0.01,0.4],r=[0.005,0.25],i=1 \ldots k$$
LFR Background $$\tau _1=[3,2], \tau _2=(1,1.9], \mu =[0.1,0.4], \langle d \rangle =[32,256]$$, $$d_{\max }=[256,2048],\min _{c}=[256,1000], \max _{c}=[512,2000]$$
ER Foreground $$n_f=\{30,40,80\},k_f=\{1,2,4\},p_f=[0.5,1]$$
1. Number of nodes is represented by $$N=4000$$. SBM parameters are: k represents the number of communities, $$p_{i}$$ the edge probability for within-community i, r the across-community edge probability, such that $$p_{i} > r$$. LFR parameters are: $$\tau _1,\tau _2$$ skewness parameters for degree and cluster size distributions respectively, $$\langle d \rangle$$ represents the average network degree, $$d_{\min },d_{\max }$$ represent the min and max values of degree distribution, $$\min _c$$ and $$\max _c$$ represent the sizes of smallest and largest clusters, and finally $$n_f,k_f,p_f$$ represent the size of the foreground subnetwork, number of foreground subnetworks and its edge probability, respectively