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Publications

Displaying results 351 to 360 of 681.

  1. Dikshant Gupta; Matthias Klusch

    Hybrid Deep Reinforcement Learning and Planning for Safe and Comfortable Automated Driving

    In: Intelligent Vehicles. IEEE Intelligent Vehicles Symposium (IV-2023), IEEE, 2023.

  2. Md Abdul Kadir; Abdulrahman Mohamed Selim; Michael Barz; Daniel Sonntag

    A User Interface for Explaining Machine Learning Model Explanations

    In: Companion Proceedings of the 28th International Conference on Intelligent User Interfaces. International Conference on Intelligent User Interfaces (IUI-2023), March 27-31, Sydney, NSW, Australia, Pages 59-63, IUI'23 Companion, Vol. Companion Proceedings of the 28th International Conference on Intelligent User Interfaces, ISBN 9798400701078, Association for Computing Machinery, New York, NY, United States, 3/2023.

  3. Dominique Mercier; Andreas Dengel; Sheraz Ahmed

    From Private to Public: Benchmarking GANs in the Context of Private Time Series Classification

    In: Applied Intelligence (APIN), Vol. July 2024, Pages 1-15, Springer Nature, 7/2023.

  4. Amos Smith; Jeremy Coffelt; Kai Lingemann

    A Deep Learning Framework for Semantic Segmentation of Underwater Environments

    In: OCEANS 22 Hampton Roads. OCEANS MTS/IEEE Conference (OCEANS-2022), October 17-20, Hampton Roads, VA, USA, IEEE, 10/2022.

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

    HJB optimal feedback control with deep differential value functions and action constraints

    In: Leslie Pack Kaelbling; Danica Kragic; Komei Sugiura (Hrsg.). 3rd Annual Conference on Robot Learning. Conference on Robot Learning (CoRL-2019), October 30 - November 1, Osaka, Japan, Pages 640-650, Proceedings of Machine Learning Research (PMLR), Vol. 100, PMLR, 2019.

  6. 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.

  7. Bastian Wibranek; Yuxi Liu; Niklas Funk; Boris Belousov; Jan Peters; Oliver Tessmann

    Reinforcement learning for sequential assembly of SL-blocks-self-interlocking combinatorial design based on machine learning

    In: Vesna Stojaković; Bojan Tepavčević (Hrsg.). eCAADe 2021 - Towards a New, Configurable Architecture, Volume 1 - Proceedings. Education and Research in Computer Aided Architectural Design in Europe (eCAADe-2021), September 8-10, Novi Sad, Serbia, Pages 27-36, eCAADe, 2021.

  8. Boris Belousov; Bastian Wibranek; Jan Schneider; Tim Schneider; Georgia Chalvatzaki; Jan Peters; Oliver Tessmann

    Robotic architectural assembly with tactile skills: Simulation and optimization

    In: Automation in Construction, Vol. 133, Pages 1-10, Elsevier, 1/2022.

  9. Fabio Muratore; Theo Gruner; Florian Wiese; Boris Belousov; Michael Gienger; Jan Peters

    Neural posterior domain randomization

    In: Aleksandra Faust; David Hsu; Gerhard Neumann (Hrsg.). Proceedings of the 5th Conference on Robot Learning. Conference on Robot Learning (CoRL-2021), November 8-11, London, United Kingdom, Pages 1532-1542, Proceedings of Machine Learning Research (PMLR), Vol. 164, PMLR, 2022.

  10. Rustam Galljamov; Guoping Zhao; Boris Belousov; André Seyfarth; Jan Peters

    Improving Sample Efficiency of Example-Guided Deep Reinforcement Learning for Bipedal Walking

    In: IEEE-RAS International Conference on Humanoid Robots. IEEE-RAS International Conference on Humanoid Robots (Humanoids-2022), November 28-30, Ginowan, Okinawa, Japan, Pages 587-593, IEEE, 2022.

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