r activations are informative on both input and excitations of a layer.</p>
<p>(a) Gradients (10 steps)</p>
<p>(a) “Speech”</p>
<h2 id="images-as-sound">Images as Sound</h2>
<p>The creative potential of these projects lives in their experimental approach towards spectral transformation. In all these cases, the authors perform layer <em>activation maximization</em> on a deep network trained on images, taking the gradient between the activations triggered by an image and the input. The input, in this case