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Forward-Inverse SIR model networks. Each network contains 1 input node (time t), one1output node (value), 4 hidden layers, and 256 nodes in each hidden layer. The hyperbolic tangent tanh(x) is used in the activation functions except for the last layer. The Softplus and Sigmoid functions are used in the last hidden layer to meet the constraints S, I, R, β>0, and 0<γ<1. I: infected; R: recovered; S: susceptible.
