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Publications

 

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Displaying results 1 to 10 of 77.
  1. Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting

    Neuro-Symbolic Forward Reasoning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2110.09383, Pages 0-10, arXiv, 2021.

  2. Zhongjie Yu; Fabrizio Ventola; Kristian Kersting

    Whittle Networks: A Deep Likelihood Model for Time Series

    In: Marina Meila; Tong Zhang (Hrsg.). Proceedings of the 38th International Conference on Machine Learning. International Conference on Machine …

  3. Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting With Their Explanations

    In: IEEE Conference on Computer Vision and Pattern Recognition. International Conference on Computer Vision and Pattern Recognition (CVPR-2021), June …

  4. Xiaoting Shao; Arseny Skryagin; Wolfgang Stammer; Patrick Schramowski; Kristian Kersting

    Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions

    In: Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021. AAAI Conference on Artificial Intelligence (AAAI-2021), Pages 9533-9540, AAAI …

  5. Christopher Metz; Mehran Goli; Rolf Drechsler

    Pick the Right Edge Device: Towards Power and Performance Estimation of CUDA-based CNNs on GPGPUs

    In: Proceedings of SLOHA Workshop 2021. System-level Design Methods for Deep Learning on Heterogeneous Architectures (SLOHA-2021), located at Design, …

  6. Dennis Stumpf; Stephan Krauß; Gerd Reis; Oliver Wasenmüller; Didier Stricker

    SALT: A Semi-automatic Labeling Tool for RGB-D Video Sequences

    In: Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. International …

  7. Max Leimkühler; Laura Gravemeier; Tim Biester; Oliver Thomas

    Deep learning object detection as an assistance system for complex image labeling tasks

    In: Proceedings of the 54th Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences (HICSS-2021), A …

  8. Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring

    In: Witold Pedrycz; Shyi-Ming Chen (Hrsg.). Interpretable Artificial Intelligence: A Perspective of Granular Computing. Chapter 1, Pages 1-28, Vol. …

  9. Ho Minh Duy Nguyen; Duy M. Nguyen; Huong Vu; Binh T. Nguyen; Fabrizio Nunnari; Daniel Sonntag

    An Attention Mechanism using Multiple Knowledge Sources for COVID-19 Detection from CT Images

    In: The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21). AAAI Conference on Artificial Intelligence (AAAI), Workshop on Trustworthy …

  10. TSInsight: A local-global attribution framework for interpretability in time-series data

    In: Sensors - Open Access Journal (Sensors), Vol. 21, Pages 1-16, MDPI, 11/2021.