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Jahr: 2020
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  1. Alejandro Molina; Patrick Schramowski; Kristian Kersting

    Padé Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks

    In: 8th International Conference on Learning Representations. International Conference on Learning Representations (ICLR-2020), April 26-30, Addis …

  2. Ute Schmid; Volker Tresp; Matthias Bethge; Kristian Kersting; Rainer Stiefelhagen

    Künstliche Intelligenz - Die dritte Welle

    In: Ralf H. Reussner; Anne Koziolek; Robert Heinrich (Hrsg.). 50. Jahrestagung der Gesellschaft für Informatik, INFORMATIK 2020 - Back to the Future. …

  3. Amos Treiber; Alejandro Molina; Christian Weinert; Thomas Schneider; Kristian Kersting

    CryptoSPN: Privacy-Preserving Sum-Product Network Inference

    In: Giuseppe De Giacomo; Alejandro Catalá; Bistra Dilkina; Michela Milano; Senén Barro; Alberto Bugarín; Jérôme Lang (Hrsg.). 24th European Conference …

  4. Amos Treiber; Alejandro Molina; Christian Weinert; Thomas Schneider; Kristian Kersting

    CryptoSPN: Expanding PPML beyond Neural Networks

    In: Benyu Zhang; Raluca Ada Popa; Matei Zaharia; Guofei Gu; Shouling Ji (Hrsg.). PPMLP'20: Proceedings of the 2020 Workshop on Privacy-Preserving …

  5. Patrick Schramowski; Wolfgang Stammer; Stefano Teso; Anna Brugger; Franziska Herbert; Xiaoting Shao; Hans-Georg Luigs; Anne-Katrin Mahlein; Kristian Kersting

    Making deep neural networks right for the right scientific reasons by interacting with their explanations

    In: Nature Machine Intelligence, Vol. 2, No. 8, Pages 476-486, Springer, 2020.

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

    The Moral Choice Machine

    In: Frontiers in Artificial Intelligence, Vol. 3, Pages 0-10, Frontiers, 2020.

  7. Johannes Czech; Moritz Willig; Alena Beyer; Kristian Kersting; Johannes Fürnkranz

    Learning to Play the Chess Variant Crazyhouse Above World Champion Level With Deep Neural Networks and Human Data

    In: Frontiers in Artificial Intelligence, Vol. 3, Pages 0-10, Frontiers, 2020.

  8. Melvin Laux; Oleg Arenz; Jan Peters; Joni Pajarinen

    Deep Adversarial Reinforcement Learning for Object Disentangling

    In: IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems …

  9. Nils Rottmann; Tjasa Kunavar; Jan Babic; Jan Peters; Elmar Rueckert

    Learning Hierarchical Acquisition Functions for Bayesian Optimization

    In: IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems …

  10. Julen Urain; Michele Ginesi; Davide Tateo; Jan Peters

    ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows

    In: IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems …

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