Hey everyone,

I am trying out neural PDE to solve Euler’s equations in 1D. In my problem, I have two inputs : t and x, and I have three outputs : density ρ, velocity v and pressure p. Here are the equations:

\partial_t \rho + \rho~\partial_x v + v~\partial_x \rho = 0

\partial_t v + v~\partial_x v + \partial_x p / \rho = 0

\partial_t p + v~\partial_x p + \gamma p~\partial_x v = 0

I have noticed that in NeuralPDE, you always use neural networks with one output, so in this problem, I would need to train three different neural networks for each of my output quantities. Is it possible to use only one neural network with three outputs in NeuralPDE?

Thank you for yout answers!