Training of a universal differential equation on multiple initial states and mini-batches

General Usage
1

Hi,
I am training a UDE controlled by an input signal as part of my thesis. To be able to get a more generalized neural network on multiple data, I want to train on around 1000 different initial states and use mini-batches on the go.
I was not able to find some example of training with multiple initial states so far. Is there any available? If not, what approach should be used?

Many thanks in advance

2

It’s very common to do it, but yeah… I’m surprised… I don’t see a tutorial on it :sweat_smile:. Did you end up writing something? I’d like to make sure we make it into a tutorial