continuous_time_identification (Burgers)

[omerbme]

Why do you use exp for lambda_2
def net_f(self, x, t): lambda_1 = self.lambda_1 lambda_2 = tf.exp(self.lambda_2) u = self.net_u(x,t) u_t = tf.gradients(u, t)[0] u_x = tf.gradients(u, x)[0] u_xx = tf.gradients(u_x, x)[0] f = u_t + lambda_1*u*u_x - lambda_2*u_xx

[amiralizadeh1]

I have the same question!

[nish-ant]

It's been discussed here: #34

[Roy-fyq]

make sure that lambda2 always is positive