ualization of the fake samples. This visualization shows how the generator learns a mapping function to make its output look similar to the distribution of the <span style="color: var(--real-data-color);">real samples</span>.
    </p>
    
    <div class="supporting-figure">
      <img src="figures/figure-generator-transformation.png" />
      <div class="figure-caption">
        Figure 3. The generator's data transformation is visualized as a manifold, which turns input noise (leftmost) into fake samples (