Papers
Controllably Sparse Perturbations of Robust Classifiers for Explaining Predictions and Probing Learned Concepts
Jay Roberts and Theodoros Tsiligkaridis
Revealing Multimodality in Ensemble Weather Prediction
Natacha Galmiche, Helwig Hauser, Thomas Spengler, Clemens Spensberger, Morten Brun, and Nello Blaser

Recent Submissions

  • Revealing Multimodality in Ensemble Weather Prediction 

    Galmiche, Natacha; Hauser, Helwig; Spengler, Thomas; Spensberger, Clemens; Brun, Morten; Blaser, Nello (The Eurographics Association, 2021)
    Ensemble methods are widely used to simulate complex non-linear systems and to estimate forecast uncertainty. However, visualizing and analyzing ensemble data is challenging, in particular when multimodality arises, i.e., ...
  • MLVis 2021: Frontmatter 

    Archambault, Daniel; Nabney, Ian; Peltonen, Jaakko (The Eurographics Association, 2021)
  • Controllably Sparse Perturbations of Robust Classifiers for Explaining Predictions and Probing Learned Concepts 

    Roberts, Jay; Tsiligkaridis, Theodoros (The Eurographics Association, 2021)
    Explaining the predictions of a deep neural network (DNN) in image classification is an active area of research. Many methods focus on localizing pixels, or groups of pixels, which maximize a relevance metric for the ...