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Jahr: 2019
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  1. Badarinath Katti; Christiane Plociennik; Michael Schweitzer

    A Jumpstart Framework for Semantically Enhanced OPC-UA

    In: KI - Künstliche Intelligenz, German Journal on Artificial Intelligence - Organ des Fachbereiches "Künstliche Intelligenz" der Gesellschaft für Informatik e.V. (KI), Vol. 33, No. 2, Pages 131-140, Springer, 2019.

  2. Max Birtel; Alexander David; Jesko Hermann; Florian Mohr; Martin Ruskowski

    FutureFit: a strategy for getting a production asset to an industry 4.0 component – a human-centered approach

    In: Procedia Manufacturing, Vol. 38, Pages 1000-1007, ELSEVIER, 2019.

  3. Ralph Bergmann; Mirko Lenz; Stefan Ollinger; Maximilian Pfister

    Similarity Measures for Case-Based Retrieval of Natural Language Argument Graphs in Argumentation Machines

    In: Proceedings of the Thirty-Second International Florida Artificial Intelligence Research Society Conference. International FLAIRS Conference (FLAIRS-2019), Sarasota, Florida, USA, Pages 329-334, AAAI Press, 2019.

  4. Mirko Lenz; Stefan Ollinger; Premtim Sahitaj; Ralph Bergmann

    Semantic Textual Similarity Measures for Case-Based Retrieval of Argument Graphs

    In: Case-Based Reasoning Research and Development. International Conference on Case-Based Reasoning (ICCBR-2019), Otzenhausen, Germany, Pages 219-234, Lecture Notes in Computer Science (LNCS), Vol. 11680, ISBN 978-3-030-29249-2, Springer International Publishing, Cham, 2019.

  5. Patrick Schramowski; Cigdem Turan; Sophie F. Jentzsch; Constantin A. Rothkopf; Kristian Kersting

    BERT has a Moral Compass: Improvements of ethical and moral values of machines

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1912.05238, Pages 0-10, arXiv, 2019.

  6. Fabrizio Ventola; Karl Stelzner; Alejandro Molina; Kristian Kersting

    Random Sum-Product Forests with Residual Links

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1908.03250, Pages 0-10, arXiv, 2019.

  7. Alejandro Molina; Antonio Vergari; Karl Stelzner; Robert Peharz; Pranav Subramani; Nicola Di Mauro; Pascal Poupart; Kristian Kersting

    SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1901.03704, Pages 0-10, arXiv, 2019.

  8. Robert Peharz; Antonio Vergari; Karl Stelzner; Alejandro Molina; Martin Trapp; Xiaoting Shao; Kristian Kersting; Zoubin Ghahramani

    Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning

    In: Amir Globerson; Ricardo Silva (Hrsg.). Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence. Conference in Uncertainty in Artificial Intelligence (UAI-2019), July 22-25, Tel Aviv, Israel, Pages 334-344, Proceedings of Machine Learning Research, Vol. 115, AUAI Press, 2019.

  9. Claas Völcker; Alejandro Molina; Johannes Neumann; Dirk Westermann; Kristian Kersting

    DeepNotebooks: Deep Probabilistic Models Construct Python Notebooks for Reporting Datasets

    In: Peggy Cellier; Kurt Driessens (Hrsg.). Machine Learning and Knowledge Discovery in Databases. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD-2019), International Workshops of ECML PKDD 2019, Proceedings, Part I, September 16-20, Würzburg, Germany, Pages 28-43, Communications in Computer and Information Science, Vol. 1167, Springer, 2019.

  10. Navdeep Kaur; Gautam Kunapuli; Saket Joshi; Kristian Kersting; Sriraam Natarajan

    Neural Networks for Relational Data

    In: Dimitar Kazakov; Can Erten (Hrsg.). Inductive Logic Programming - 29th International Conference, Proceedings. International Conference on Inductive Logic Programming (ILP-2019), September 3-5, Plovdiv, Bulgaria, Pages 62-71, Lecture Notes in Computer Science (LNAI), Vol. 11770, Springer, 2019.

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