张元馨

``` def pde(x, y): dy_x = dde.grad.jacobian(y, x, i=0, j=0) dy_t = dde.grad.jacobian(y, x, i=0, j=1) dy_xx = dde.grad.hessian(y, x, i=0, j=0) return dy_t + y * dy_x - 0.01...

> You cannot use `model.predict` in PDE definition. I want to use two networks, where the prediction value of one network appears in the loss function of the other network....