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Applied Network Science

Table 10 Comparison of training time (minutes) between ML-GAT, ML-GCN, GrAMME-SG and GrAMME-Fusion

From: Graph convolutional and attention models for entity classification in multilayer networks

Network

ML-GAT

ML-GCN

GrAMME-SG

GrAMME-Fusion

Balance

0.2935

0.1270

12.9228

12.7558

CKM-Social

0.2465

0.1275

3.0005

2.6893

DKPol

0.2626

0.1798

7.2329

6.2134

Leskovec-Ng

0.2632

0.1269

3.1790

2.4235

Vickers

0.2663

0.1255

0.3158

0.3242

Koumbia-2-mpx

0.2705

0.1727

52.3738

44.1908

  1. The training was performed on Google Colab with Tesla T4 GPU with the same hyperparameter setting described in "Experimental settings" section
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