Applied Network Science

Table 3 Results with Kuramoto model

From: A general deep learning framework for network reconstruction and dynamics learning

Node Num	State	LSTM	NRI				GGN
		MSE	ACC	TPR	FPR	MSE	ACC	TPR	FPR	MSE
10	coherent	2.67e-2	0.518	0.543	0.505	9.63e-2	0.998	0.994	0.004	1.12e-3
10	incoherent	2.85e-2	0.517	0.543	0.508	1.11e-1	0.998	0.994	0.004	8.36e-4
30	coherent	3.12e-2	-	-	-	-	0.898	0.920	0.169	3.96e-4
30	incoherent	3.35e-2	-	-	-	-	0.81	0.700	0.124	1.90e-4

The bold text represented the best results of a series of experiments

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