Machine Learning Methods in Visualisation for Big Data 2021

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Papers

Controllably Sparse Perturbations of Robust Classifiers for Explaining Predictions and Probing Learned Concepts

] [meta data

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Jay Roberts and Theodoros Tsiligkaridis

Revealing Multimodality in Ensemble Weather Prediction

] [meta data

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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 ...