Now showing items 1-2 of 2

    • ViNNPruner: Visual Interactive Pruning for Deep Learning 

      Schlegel, Udo; Schiegg, Samuel; Keim, Daniel A. (The Eurographics Association, 2022)
      Neural networks grow vastly in size to tackle more sophisticated tasks. In many cases, such large networks are not deployable on particular hardware and need to be reduced in size. Pruning techniques help to shrink deep ...
    • Visual Exploration of Neural Network Projection Stability 

      Bredius, Carlo; Tian, Zonglin; Telea, Alexandru (The Eurographics Association, 2022)
      We present a method to visually assess the stability of deep learned projections. For this, we perturb the high-dimensional data by controlled sequences and visualize the resulting changes in the 2D projection. We apply ...