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Jahr: 2019
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  1. Hans-Jürgen Profitlich; Daniel Sonntag

    Interactivity and Transparency in Medical Risk Assessment with Supersparse Linear Integer Models

    BMBF, DFKI Research Reports (RR), Vol. abs/1911.12119, ArXiv, 2019.

  2. Michael Barz; Daniel Sonntag

    Incremental Improvement of a Question Answering System by Re-ranking Answer Candidates using Machine Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1908.10149, Pages 1-13, arXiv, 8/2019.

  3. Shivesh Kumar

    Modular and Analytical Methods for Solving Kinematics and Dynamics of Series-Parallel Hybrid Robots

    PhD-Thesis, Universität Bremen: Informatik/Mathematik, 11/2019.

  4. Kumar Shridhar; Joonho Lee; Hideaki Hayashi; Purvanshi Mehta; Brian Kenji Iwana; Seokjun Kang; Seiichi Uchida; Sheraz Ahmed; Andreas Dengel

    ProbAct: A Probabilistic Activation Functionfor Deep Neural Networks

    In: OPT2020: 12th Annual Workshop on Optimization for Machine Learning. Workshop on Optimization for Machine Learning (OPT-2020), located at NeurIPS2020, December 11-12, Vancouver, Canada, ArXiv, 2019.

  5. Andreas Dengel

    Some Shades of Grey!: Interpretability and Explainability of Deep Neural Networks

    In: Proceedings WCRML19. ACM Workshop on Crossmodal Learning and Application, Ottawa, Canada, ISBN 978-1-4503-6780-6, Association for Computing Machinery, New York, 6/2019.

  6. Andreas Dengel; Richard Socher; Elsa Andrea Kirchner; Shirley Ogolla

    Künstliche Intelligenz: Die Zukunft von Mensch und Maschine

    ZEIT Akademie, 2019.

  7. Marcel Kolbe; Pascal Reuß; Jakob Michael Schönborn; Klaus-Dieter Althoff

    Conceptualization and Implementation of a Reinforcement Learning Approach Using a Case-Based Reasoning Agent in a FPS Scenario

    In: Robert Jäschke; Matthias Weidlich (Hrsg.). Lernen, Wissen, Daten, Analysen. GI-Workshop-Tage "Lernen, Wissen, Daten, Analysen" (LWDA-2019), September 30 - October 2, Berlin, Germany, Pages 280-291, CEUR, 2019.

  8. Viktor Eisenstadt; Klaus-Dieter Althoff

    Overview of the 4R CBR Cycle Modifications (Extended Version)

    In: Robert Jäschke; Matthias Weidlich (Hrsg.). Lernen, Wissen, Daten, Analysen. GI-Workshop-Tage "Lernen, Wissen, Daten, Analysen" (LWDA-2019), Proceedings of the Conference on "Lernen, Wissen, Daten, Analysen", September 30 - October 2, Berlin, Germany, Pages 230-240, CEUR, 2019.

  9. Viktor Eisenstadt; Christoph Lanhgenhan; Klaus-Dieter Althoff

    Supporting Architectural Design Process with FLEA - A Distributed AI Methodology for Retrieval, Suggestion, Adaptation, and Explanation of Room Configurations

    In: Ji-Hyun Lee (Hrsg.). Computer-Aided Architectural Design. "Hello, Culture". CAAD Futures, June 26-28, Daejeon, Korea, Republic of, Pages 58-73, Springer, Singapore, 2019.

  10. Oliver Berg; Pascal Reuß; Rotem Stram; Klaus-Dieter Althoff

    Comparing Similarity Learning with Taxonomies and One-Mode Projection in Context of the FEATURE-TAK Framework

    In: Kerstin Bach; Cindy Marling (Hrsg.). Case-Based Reasoning Research and Development. International Conference on Case-Based Reasoning (ICCBR-2019), September 8-12, Otzenhausen, Germany, Pages 01-16, Springer, 2019.

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