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    On KDE-based Brushing in Scatterplots and how it Compares to CNN-based Brushing 

    Fan, Chaoran; Hauser, Helwig (The Eurographics Association, 2019)
    In this paper, we investigate to which degree the human should be involved into the model design and how good the empirical model can be with more careful design. To find out, we extended our previously published Mahalanobis ...
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    Interpreting Black-Box Semantic Segmentation Models in Remote Sensing Applications 

    Janik, Adrianna; Sankaran, Kris; Ortiz, Anthony (The Eurographics Association, 2019)
    In the interpretability literature, attention is focused on understanding black-box classifiers, but many problems ranging from medicine through agriculture and crisis response in humanitarian aid are tackled by semantic ...
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    Visual Analysis of the Impact of Neural Network Hyper-Parameters 

    Jönsson, Daniel; Eilertsen, Gabriel; Shi, Hezi; Zheng, Jianmin; Ynnerman, Anders; Unger, Jonas (The Eurographics Association, 2020)
    We present an analysis of the impact of hyper-parameters for an ensemble of neural networks using tailored visualization techniques to understand the complicated relationship between hyper-parameters and model performance. ...
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    Visual Analysis of Multivariate Urban Traffic Data Resorting to Local Principal Curves 

    Silva, Carla; d'Orey, Pedro; Aguiar, Ana (The Eurographics Association, 2019)
    Traffic congestion causes major economic, environmental and social problems in modern cities. We present an interactive visualization tool to assist domain experts on the identification and analysis of traffic patterns at ...
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    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., ...
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    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 ...
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    ModelSpeX: Model Specification Using Explainable Artificial Intelligence Methods 

    Schlegel, Udo; Cakmak, Eren; Keim, Daniel A. (The Eurographics Association, 2020)
    Explainable artificial intelligence (XAI) methods aim to reveal the non-transparent decision-making mechanisms of black-box models. The evaluation of insight generated by such XAI methods remains challenging as the applied ...
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    Visual Interpretation of DNN-based Acoustic Models using Deep Autoencoders 

    Grósz, Tamás; Kurimo, Mikko (The Eurographics Association, 2020)
    In the past few years, Deep Neural Networks (DNN) have become the state-of-the-art solution in several areas, including automatic speech recognition (ASR), unfortunately, they are generally viewed as black boxes. Recently, ...
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    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 ...
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    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 ...

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    AuthorHauser, Helwig (2)Keim, Daniel A. (2)Aguiar, Ana (1)Blaser, Nello (1)Brun, Morten (1)Cakmak, Eren (1)d'Orey, Pedro (1)Eilertsen, Gabriel (1)Fan, Chaoran (1)Galmiche, Natacha (1)... View MoreSubject
    Computing methodologies (10)
    centered computing (6)Human (6)Neural networks (4)Visual analytics (4)Artificial intelligence (2)Human centered computing (2)Applied computing (1)CCS Concepts: Human-centered computing --> Visual analytics; Computing methodologies --> Neural networks (1)CCS Concepts: Human-centered computing --> Visualization techniques; Computing methodologies --> Neural networks (1)... View MoreDate Issued2019 (3)2020 (3)2021 (2)2022 (2)Has File(s)true (10)

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    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
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    TUGFhA