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Year: 2019
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Displaying results 31 to 40 of 574.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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 …

  8. 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 …

  9. 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 …

  10. Karl Stelzner; Robert Peharz; Kristian Kersting

    Faster Attend-Infer-Repeat with Tractable Probabilistic Models

    In: Kamalika Chaudhuri; Ruslan Salakhutdinov (Hrsg.). Proceedings of the 36th International Conference on Machine Learning. International Conference …

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