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Publications

 

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Displaying results 11 to 20 of 126.
  1. Anna Brugger; Jan Behmann; Stefan Paulus; Hans-Georg Luigs; Matheus Thomas Kuska; Patrick Schramowski; Kristian Kersting; Ulrike Steiner; Anne-Katrin Mahlein

    Extending Hyperspectral Imaging for Plant Phenotyping to the UV-Range

    In: Remote Sensing, Vol. 11, No. 12, Pages 0-10, MDPI, 2019.

  2. Fabrizio Riguzzi; Kristian Kersting; Marco Lippi; Sriraam Natarajan

    Editorial: Statistical Relational Artificial Intelligence

    In: Frontiers in Robotics and AI, Vol. 6, Pages 0-10, Frontiers, 2019.

  3. Nils M. Kriege; Marion Neumann; Christopher Morris; Kristian Kersting; Petra Mutzel

    A unifying view of explicit and implicit feature maps of graph kernels

    In: Data Mining and Knowledge Discovery, Vol. 33, No. 6, Pages 1505-1547, Springer, 2019.

  4. Laura Antanas; Plinio Moreno; Marion Neumann; Rui Pimentel de Figueiredo; Kristian Kersting; José Santos-Victor; Luc De Raedt

    Semantic and geometric reasoning for robotic grasping: a probabilistic logic approach

    In: Autonomous Robots, Vol. 43, No. 6, Pages 1393-1418, Springer, 2019.

  5. Michael Benedikt; Kristian Kersting; Phokion G. Kolaitis; Daniel Neider

    Logic and Learning (Dagstuhl Seminar 19361)

    In: Dagstuhl Reports, Vol. 9, No. 9, Pages 1-22, Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2019.

  6. 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.

  7. 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.

  8. 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.

  9. 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 …

  10. Manisha Luthra; Boris Koldehofe; Ralf Steinmetz

    Transitions for Increased Flexibility in Fog Computing: A Case Study on Complex Event Processing

    In: Informatik Spektrum, Vol. 42, No. 4, Pages 244-255, Springer, 2019.