I am used to train neural networks that are designed for generation, such as GANs or VAEs.
I am wondering what are the common techniques to generate data that would minimize the target/energy learned by a regression model, following the idea of Deep Dream.
I can think of two ways :
1) Use the trained regression neural network as a loss function (with its gradients) for another neural network that is trained to produce structures that produce a given energy / target, as given by the first neural network.
2) Use an standard optimization algorithm (not a neural network) to find which inputs minimize the output of the regression model.
Are there any other common methods to do this ? What are the most know / effective methods ?
Any idea / reference would be great !