<p>There is some work around that, starting with the paper of <a href="https://arxiv.org/abs/1312.6034" rel="nofollow noreferrer">Simoyan</a> and that have been popularized with the "Deep Dream" buzz about 2/3 years ago. The basic idea is to start from a random image and optimize on the <em>input data</em>, rather than the network itself. So in your case, you would optimize the image to maximize the probability of the image being recognized as a cat.</p>

<p>Alas, a classifier is not a generator, and therefore as you may recall from all the "deep dream" movies, the resulting images are all but realistic. (You can find such images in the paper cited above). Realistic sample generation, if that is your goal, is nowadays often achieved with GANs and their variants.</p>
Ask a machine learning retrained model "what this thing looks like for you ?"
<p>In a classifying image context (Tensorflow), imagine you have a retrained model with animals for example, is it possible to "ask" what a cat looks like for your model ? 
I don't want to give it a picture and it recognizes a cat, I want it to "describe" what a cat is.
I was just wondering...
Thanks ! =D</p>