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Table 1 Results with Boolean Network

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

Node NumStateLSTMNRIGGN
  ACC(dyn)ACC(net)TPRFPRACC(dyn)ACC(net)TPRFPRACC(dyn)
10non-chaotic0.8410.5680.4220.3950.8200.99110.0080.694
10chaotic0.7890.4810.4580.4650.5280.9940.98300.693
30non-chaotic0.9120.4090.5900.5910.7980.9260.4760.0360.948
30chaotic0.7650.4600.5490.5470.7210.90.6010.0340.699
100non-chaotic0.933----0.840.5050.1530.982
100chaotic0.796----0.9570.250.0130.7483
  1. The bold text represented the best results of a series of experiments