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  1. Daniel Tanneberg; Jan Peters; Elmar Rueckert

    Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks

    In: Neural Networks, Vol. 109, Pages 67-80, Elsevier, 2019.

  2. Simone Parisi; Voot Tangkaratt; Jan Peters; Mohammad Emtiyaz Khan

    TD-regularized actor-critic methods

    In: Machine Learning, Vol. 108, No. 8-9, Pages 1467-1501, Springer, 2019.

  3. Joni Pajarinen; Hong Linh Thai; Riad Akrour; Jan Peters; Gerhard Neumann

    Compatible natural gradient policy search

    In: Machine Learning, Vol. 108, No. 8-9, Pages 1443-1466, Springer, 2019.

  4. Carlos Celemin; Guilherme Maeda; Javier Ruiz-del-Solar; Jan Peters; Jens Kober

    Reinforcement learning of motor skills using Policy Search and human corrective advice

    In: International Journal of Robotics Research (IJRR), Vol. 38, No. 14, Pages 0-10, Sage Publications, 2019.

  5. Marco Ewerton; Oleg Arenz; Guilherme Maeda; Dorothea Koert; Zlatko Kolev; Masaki Takahashi; Jan Peters

    Learning Trajectory Distributions for Assisted Teleoperation and Path Planning

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

  6. Tim Schürmann; Betty J. Mohler; Jan Peters; Philipp Beckerle

    How Cognitive Models of Human Body Experience Might Push Robotics

    In: Frontiers in Neurorobotics, Vol. 13, Pages 0-10, Frontiers, 2019.

  7. 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.

  8. 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.

  9. 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.

  10. 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.