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Publications

Displaying results 161 to 170 of 672.

  1. Guillaume Duret; Mohamed Mahmoud Sayed Shelkamy Ali; Nicolas Cazin; Danylo Mazurak; Anna Samsonenko; Alexandre Chapin; Florence Zara; Emmanuel Dellandréa; Liming Chen; Jan Peters

    FruitBin: A Tunable Large-Scale Dataset for Advancing 6D Pose Estimation in Fruit Bin-Picking Automation

    In: Alessio Del Bue; Cristian Canton; Jordi Pont-Tuset; Tatiana Tommasi (Hrsg.). Computer Vision - ECCV 2024 Workshops - Milan, Italy, September 29-October 4, 2024, Proceedings, Part I. Computer Vision Systems (CVS), Pages 73-90, Lecture Notes in Computer Science, Vol. 15623, Springer, 2024.

  2. Julen Urain; Ajay Mandlekar; Yilun Du; Mahi Shafiullah; Danfei Xu; Katerina Fragkiadaki; Georgia Chalvatzaki; Jan Peters

    Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2408.04380, Pages 1-20, arXiv, 2024.

  3. Luca Lach; Robert Haschke; Davide Tateo; Jan Peters; Helge J. Ritter; Júlia Borràs Sol; Carme Torras

    Zero-Shot Transfer of a Tactile-based Continuous Force Control Policy from Simulation to Robot

    In: IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2024, Abu Dhabi, United Arab Emirates, October 14-18, 2024. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Pages 725-732, IEEE, 2024.

  4. Piotr Kicki; Puze Liu; Davide Tateo; Haitham Bou-Ammar; Krzysztof Walas; Piotr Skrzypczynski; Jan Peters

    Fast Kinodynamic Planning on the Constraint Manifold With Deep Neural Networks

    In: IEEE Transactions on Robotics (T-RO), Vol. 40, Pages 277-297, IEEE, 2024.

  5. Daniel Palenicek; Florian Vogt; Joe Watson; Ingmar Posner; Jan Peters

    XQC: Well-conditioned Optimization Accelerates Deep Reinforcement Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2509.25174, Pages 1-24, arXiv, 2025.

  6. Dan Hudson; Jurgen van den Hoogen; Stefan Bloemheuvel; Martin Atzmueller

    Stay Tuned! Analysing Hyperparameters of a Wide-Kernel Architecture for Industrial Faults

    In: Proceedings 2024 IEEE Conference on Artificial Intelligence (CAI). IEEE Conference on Artificial Intelligence (CAI-2024), June 25-27, Marina Bay Sands, Singapore, Pages 1350-1356, IEEE Xplore, 2024.

  7. Jurgen Van Den Hoogen; Dan Hudson; Martin Atzmueller

    Data-Hungry Fault Detection Algorithms Can Try Transfer Learning for Starters

    In: Proc. IEEE International Conference on Data Engineering Workshops (ICDEW). IEEE International Conference on Data Engineering (ICDE-2024), Pages 91-95, IEEE, 2024.

  8. Harihara Bharathy Swaminathan; Aron Sommer; Uri Iurgel; Andreas Becker; Martin Atzmüller

    Change Detection in Automotive Radar Based Occupancy Maps Using Siamese Networks

    In: 2024 International Radar Symposium (IRS). International Radar Symposium (IRS-2024), located at Microwave and Radar Week (MRW 2024), July 2-4, Poland, Pages 56-61, IEEE, 2024.

  9. Ankur Bhatt; Ko Watanabe; Jayasankar Santhosh; Andreas Dengel; Shoya Ishimaru

    Estimating Self-Confidence in Video-Based Learning Using Eye-Tracking and Deep Neural Networks

    In: IEEE Access (IEEE), Vol. 12, Pages 192219-192229, IEEE, 2024.

  10. Nijat Mehdiyev; Maxim Majlatow; Peter Fettke

    Augmenting post-hoc explanations for predictive process monitoring with uncertainty quantification via conformalized Monte Carlo dropout

    In: Data & Knowledge Engineering (DKE), Vol. 156 (March 2025), Pages 1-29, Elsevier B.V. 12/2024.

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