In TensorFlow it is pretty straight forward to visualize filters and activation layers given a single input.
But I'm more interested in the opposite way: feeding a class (as one-hot vector) to the output layer and see something like the optimal input image for that specific class.
Is there a way to do so or to run the graph reversed?
Background: I'm using Googles Inception V3 with 15 classes and I've trained the network already with a large amount of data up to a good precision. Now I'm interested in understanding why and how the model distinguishes the different classes.