Thanks! @eqy. Didn’t know I could create and initialize other NN in the forward method.
Regarding “simultaneous”, I didn’t use the best word here. The idea is to create a model for each feature and predict it using the other features. Then use the last intermediate layer of each NN as input features to the final model that has to predict the real target. So the final model would have the initial features plus features engineered using the other NN.
The idea is from here https://towardsdatascience.com/automated-feature-engineering-using-neural-networks-5310d6d4280a