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Publications

Displaying results 221 to 230 of 661.
  1. Nandini Ramanan; Mayukh Das; Kristian Kersting; Sriraam Natarajan

    Discriminative Non-Parametric Learning of Arithmetic Circuits

    In: Manfred Jaeger; Thomas Dyhre Nielsen (Hrsg.). Proceedings of the 10th International Conference on Probabilistic Graphical Models. International Conference on Probabilistic Graphical Models (PGM-2020), September 23-25, Aalborg, Denmark, Pages 353-364, Proceedings of Machine Learning Research, Vol. 138, PMLR, 2020.

  2. Lukas Struppek; Dominik Hintersdorf; Daniel Neider; Kristian Kersting

    Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash

    In: FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency. ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT-22), June 21-24, Seoul, Korea, Republic of, Pages 58-69, ISBN 978-1-4503-9352-2, ACM, 2022.

  3. Donglin Wang; Anjie Qiu; Qiuheng Zhou; Hans Dieter Schotten

    A Survey on the Role of Artificial Intelligence and Machine Learning in 6G-V2X Applications

    In: Proceedings of the 11th IEEE World Forum on Internet of Things (IoT). IEEE World Forum on Internet of Things (IEEE WFIoT-2025), October 27-30, Chengdu, China, IEEE, 2025.

  4. InEKFormer: A Hybrid State Estimator for Humanoid Robots

    In: Proceedings of IEEE International Conference on Advanced Robotics (ICAR). International Conference On Advanced Robotics (ICAR-2025), December 2-5, San Juan, Argentina, Pages 833-840, IEEE, 1/2026.

  5. Informed Learning for Estimating Drought Stress at Fine-Scale Resolution Enables Accurate Yield Prediction

    In: PAIS. European Conference on Artificial Intelligence (ECAI-2025), Bologna, Italy, Pages 5384-5391, IOS Press, 2025.

  6. PALSYN: a method for synthetic multi-perspective event log generation with differential private guarantees

    In: Chiara Di Francescomarino; Marwan Hassani; Jan Mendling; Arik Senderovich (Hrsg.). Process Science, Vol. 2, No. 1, Pages 1-37, Springer Nature, Cham, 12/2025.

  7. 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.

  8. 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.

  9. 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.

  10. 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.