Table of Links
A. Empirical validation of HypNF
B. Degree distribution and clustering control in HypNF
C. Hyperparameters of the machine learning models
D. Fluctuations in the performance of machine learning models
E. Homophily in the synthetic networks
F. Exploring the parameters’ space
3.1 The S1/H2 model
Authors:
(1) Roya Aliakbarisani, this author contributed equally from Universitat de Barcelona & UBICS ([email protected]);
(2) Robert Jankowski, this author contributed equally from Universitat de Barcelona & UBICS ([email protected]);
(3) M. Ángeles Serrano, Universitat de Barcelona, UBICS & ICREA ([email protected]);
(4) Marián Boguñá, Universitat de Barcelona & UBICS ([email protected]).
This paper is
[2] The model with arbitrary dimensions has been defined in [16].
