Search Results - Höhne, Marina M.-C.

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  1. 1
    This looks More Like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation

    This looks More Like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation by Gautam, Srishti, Höhne, Marina M.-C., Hansen, Stine, Jenssen, Robert, Kampffmeyer, Michael

    Published in Pattern recognition
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  2. 2
    DeepCOMBI: explainable artificial intelligence for the analysis and discovery in genome-wide association studies

    DeepCOMBI: explainable artificial intelligence for the analysis and discovery in genome-wide association studies by Mieth, Bettina, Rozier, Alexandre, Rodriguez, Juan Antonio, Höhne, Marina M C, Görnitz, Nico, Müller, Klaus-Robert

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  3. 3
    A mathematical model-based evaluation of yeast extract’s effects on microbial growth and substrate consumption for lactic acid production by Bacillus coagulans

    A mathematical model-based evaluation of yeast extract’s effects on microbial growth and substrate consumption for lactic acid production by Bacillus coagulans by Olszewska-Widdrat, Agata, Babor, Majharulislam, Höhne, Marina M.-C., Alexandri, Maria, López-Gómez, Jose Pablo, Venus, Joachim

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  4. 4
    Demonstrating the Risk of Imbalanced Datasets in Chest X-Ray Image-Based Diagnostics by Prototypical Relevance Propagation

    Demonstrating the Risk of Imbalanced Datasets in Chest X-Ray Image-Based Diagnostics by Prototypical Relevance Propagation by Gautam, Srishti, Hohne, Marina M.-C., Hansen, Stine, Jenssen, Robert, Kampffmeyer, Michael

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  5. 5
    Finding the Right XAI Method—A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science

    Finding the Right XAI Method—A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science by Bommer, Philine Lou, Kretschmer, Marlene, Hedström, Anna, Bareeva, Dilyara, Höhne, Marina M.-C.

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  6. 6
    NoiseGrad — Enhancing Explanations by Introducing Stochasticity to Model Weights

    NoiseGrad — Enhancing Explanations by Introducing Stochasticity to Model Weights by Bykov, Kirill, Hedström, Anna, Nakajima, Shinichi, Höhne, Marina M.-C.

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  7. 7
    Visualizing the Diversity of Representations Learned by Bayesian Neural Networks

    Visualizing the Diversity of Representations Learned by Bayesian Neural Networks by Grinwald, Dennis, Bykov, Kirill, Nakajima, Shinichi, Höhne, Marina M -C

    Published in arXiv.org
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  8. 8
    Flying Adversarial Patches: Manipulating the Behavior of Deep Learning-based Autonomous Multirotors

    Flying Adversarial Patches: Manipulating the Behavior of Deep Learning-based Autonomous Multirotors by Hanfeld, Pia, Höhne, Marina M -C, Bussmann, Michael, Hönig, Wolfgang

    Published in arXiv.org
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  9. 9
    CoSy: Evaluating Textual Explanations of Neurons

    CoSy: Evaluating Textual Explanations of Neurons by Kopf, Laura, Bommer, Philine Lou, Hedström, Anna, Lapuschkin, Sebastian, Höhne, Marina M -C, Bykov, Kirill

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  10. 10
    Mark My Words: Dangers of Watermarked Images in ImageNet

    Mark My Words: Dangers of Watermarked Images in ImageNet by Bykov, Kirill, Klaus-Robert Müller, Höhne, Marina M -C

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  11. 11
    Model Guidance via Explanations Turns Image Classifiers into Segmentation Models

    Model Guidance via Explanations Turns Image Classifiers into Segmentation Models by Yu, Xiaoyan, Franzen, Jannik, Samek, Wojciech, Höhne, Marina M -C, Kainmueller, Dagmar

    Published in arXiv.org
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  12. 12
    Prototypical Self-Explainable Models Without Re-training

    Prototypical Self-Explainable Models Without Re-training by Srishti Gautam, Boubekki, Ahcene, Höhne, Marina M C, Kampffmeyer, Michael C

    Published in arXiv.org
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  13. 13
    Finding the right XAI method -- A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science

    Finding the right XAI method -- A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science by Bommer, Philine, Kretschmer, Marlene, Hedström, Anna, Bareeva, Dilyara, Höhne, Marina M -C

    Published in arXiv.org
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  14. 14
    NoiseGrad: Enhancing Explanations by Introducing Stochasticity to Model Weights

    NoiseGrad: Enhancing Explanations by Introducing Stochasticity to Model Weights by Bykov, Kirill, Hedström, Anna, Nakajima, Shinichi, Höhne, Marina M -C

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  15. 15
    Labeling Neural Representations with Inverse Recognition

    Labeling Neural Representations with Inverse Recognition by Bykov, Kirill, Kopf, Laura, Nakajima, Shinichi, Kloft, Marius, Höhne, Marina M -C

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  16. 16
    Explainable AI in Grassland Monitoring: Enhancing Model Performance and Domain Adaptability

    Explainable AI in Grassland Monitoring: Enhancing Model Performance and Domain Adaptability by Liu, Shanghua, Hedström, Anna, Basavegowda, Deepak Hanike, Weltzien, Cornelia, Höhne, Marina M -C

    Published in arXiv.org
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  17. 17
    Kidnapping Deep Learning-based Multirotors using Optimized Flying Adversarial Patches

    Kidnapping Deep Learning-based Multirotors using Optimized Flying Adversarial Patches by Hanfeld, Pia, Wahba, Khaled, Höhne, Marina M -C, Bussmann, Michael, Hönig, Wolfgang

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  18. 18
    Manipulating Feature Visualizations with Gradient Slingshots

    Manipulating Feature Visualizations with Gradient Slingshots by Bareeva, Dilyara, Höhne, Marina M -C, Warnecke, Alexander, Pirch, Lukas, Klaus-Robert Müller, Rieck, Konrad, Bykov, Kirill

    Published in arXiv.org
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  19. 19
    The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus

    The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus by Hedström, Anna, Bommer, Philine, Wickstrøm, Kristoffer K, Samek, Wojciech, Lapuschkin, Sebastian, Höhne, Marina M -C

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  20. 20
    DORA: Exploring Outlier Representations in Deep Neural Networks

    DORA: Exploring Outlier Representations in Deep Neural Networks by Bykov, Kirill, Mayukh Deb, Grinwald, Dennis, Klaus-Robert Müller, Höhne, Marina M -C

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