Before revision:  The CRNN is physically interpretable , and its weights correspond to the reaction pathways and rate constants of the chemical reaction network. Then, inferencing the reaction pathways and the rate constants are accomplished by training the equivalent CRNN via stochastic gradient descent.
After revision:  The CRNN is physically interpretable , and its weights correspond to the reaction pathways can be interpreted, and the kinetic parameters can be quantified simultaneously from the weights of the neural network. The inference of the chemical pathways is accomplished by training the equivalent CRNN via stochastic gradient descent.