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Publications

Displaying results 281 to 290 of 580.

  1. 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.

  2. 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 Uncertainty in Artificial Intelligence (UAI-2019), July 22-25, Tel Aviv, Israel, Pages 334-344, Proceedings of Machine Learning Research, Vol. 115, AUAI Press, 2019.

  3. Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting

    Neuro-Symbolic Forward Reasoning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2110.09383, Pages 0-10, arXiv, 2021.

  4. 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 Ababa, Ethiopia, OpenReview.net, 2020.

  5. Paavo Parmas; Carl Edward Rasmussen; Jan Peters; Kenji Doya

    PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos

    In: Jennifer G. Dy; Andreas Krause (Hrsg.). Proceedings of the 35th International Conference on Machine Learning. International Conference on Machine Learning (ICML-2018), July 10-15, Stockholm, Sweden, Pages 4062-4071, Proceedings of Machine Learning Research, Vol. 80, PMLR, 2018.

  6. Michael Lutter; Kim Listmann; Jan Peters

    Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems

    In: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2019), November 3-8, Macau, China, Pages 7718-7725, IEEE, 2019.

  7. Riad Akrour; Filipe Veiga; Jan Peters; Gerhard Neumann

    Regularizing Reinforcement Learning with State Abstraction

    In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2018), October 1-5, Madrid, Spain, Pages 534-539, IEEE, 2018.

  8. Saifullah Saifullah; Stefan Agne; Andreas Dengel; Sheraz Ahmed

    Analyzing the potential of active learning for document image classification

    In: International Journal on Document Analysis and Recognition (IJDAR), Vol. 26, Pages 187-209, Springer Nature, 4/2023.

  9. Mehran Jeelani; Sadbhawna; Noshaba Cheema; Klaus Illgner-Fehns; Philipp Slusallek; Sunil Jaiswal

    Expanding Synthetic Real-World Degradations for Blind Video Super Resolution

    In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. New Trends in Image Restoration and Enhancement Workshop (NTIRE-2023), 8th, located at CVPR-2023, June 18, Vancouver, BC, Canada, Pages 1199-1208, Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (CVPRW), IEEE Xplore, 6/2023.

  10. Sk Aziz Ali; Djamila Aouada; Gerd Reis; Didier Stricker (Hrsg.)

    DELO: Deep Evidential LiDAR Odometry using Partial Optimal Transport

    International Conference on Computer Vision (ICCV-2023), 2023.

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