Papers
Visual Exploration of Neural Network Projection Stability
Carlo Bredius, Zonglin Tian, and Alexandru Telea
Saliency Clouds: Visual Analysis of Point Cloud-oriented Deep Neural Networks in DeepRL for Particle Physics
Raju Ningappa Mulawade, Christoph Garth, and Alexander Wiebel
ViNNPruner: Visual Interactive Pruning for Deep Learning
Udo Schlegel, Samuel Schiegg, and Daniel A. Keim

Recent Submissions

  • Saliency Clouds: Visual Analysis of Point Cloud-oriented Deep Neural Networks in DeepRL for Particle Physics 

    Mulawade, Raju Ningappa; Garth, Christoph; Wiebel, Alexander (The Eurographics Association, 2022)
    We develop and describe saliency clouds, that is, visualization methods employing explainable AI methods to analyze and interpret deep reinforcement learning (DeepRL) agents working on point cloud-based data. The agent in ...
  • 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 ...
  • MLVis 2022: Frontmatter 

    Archambault, Daniel; Nabney, Ian; Peltonen, Jaakko (The Eurographics Association, 2022)