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Year: 2020
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Displaying results 11 to 20 of 70.

  1. 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 …

  2. 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 …

  3. Carlo D'Eramo; Davide Tateo; Andrea Bonarini; Marcello Restelli; Jan Peters

    Sharing Knowledge in Multi-Task Deep Reinforcement Learning

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

  4. Sebastián Gómez-González; Sergey Prokudin; Bernhard Schölkopf; Jan Peters

    Real Time Trajectory Prediction Using Deep Conditional Generative Models

    In: IEEE Robotics and Automation Letters (RA-L), Vol. 5, No. 2, Pages 970-976, IEEE, 2020.

  5. Michael Lutter; Debora Clever; Boris Belousov; Kim Listmann; Jan Peters

    Evaluating the Robustness of HJB Optimal Feedback Control

    In: International Symposium on Robotics. International Symposium on Robotics (ISR-2020), 52th, December 9-10, Pages 1-8, VDE, 2020.

  6. Andrea Galassi; Kristian Kersting; Marco Lippi; Xiaoting Shao; Paolo Torroni

    Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning

    In: Frontiers in Big Data, Vol. 2 - 2019, Pages 0-10, Frontiers, 1/2020.

  7. Kristian Kersting; Miryung Kim; Guy Van den Broeck; Thomas Zimmermann

    SE4ML - Software Engineering for AI-ML-based Systems (Dagstuhl Seminar 20091)

    In: Dagstuhl Reports, Vol. 10, No. 2, Pages 76-87, Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, 2020.

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

    Right for the Wrong Scientific Reasons: Revising Deep Networks by Interacting with their Explanations

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2001.05371, Pages 0-10, arXiv, 2020.

  9. Xiaoting Shao; Alejandro Molina; Antonio Vergari; Karl Stelzner; Robert Peharz; Thomas Liebig; Kristian Kersting

    Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures

    In: Manfred Jaeger; Thomas Dyhre Nielsen (Hrsg.). Proceedings of the 10th International Conference on Probabilistic Graphical Models. International …

  10. Robert Peharz; Steven Lang; Antonio Vergari; Karl Stelzner; Alejandro Molina; Martin Trapp; Guy Van den Broeck; Kristian Kersting; Zoubin Ghahramani

    Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits

    In: Proceedings of the 37th International Conference on Machine Learning. International Conference on Machine Learning (ICML-2020), July 13-18, Pages …

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