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Publikationen

Zeige Ergebnisse 811 bis 820 von 14804.

  1. Jan Speller; Malte Luttermann; Marcel Gehrke; Tanya Braun

    Compression Versus Accuracy: A Hierarchy of Lifted Models

    In: Inês Lynce; Nello Murano; Mauro Vallati; Serena Villata; Federico Chesani; Michela Milano; Andrea Omicini; Mehdi Dastani (Hrsg.). Proceedings of the Twenty-Eighth European Conference on Artificial Intelligence. European Conference on Artificial Intelligence (ECAI-2025), October 25-30, Bologna, Italy, Pages 5051-5058, Vol. 413, IOS Press, 10/2025.

  2. Jan Speller; Malte Luttermann; Marcel Gehrke; Tanya Braun

    Towards Explainability of Approximate Lifted Model Construction: A Geometric Perspective

    In: Sylvia Melzer; Hagen Peukert; Stefan Thiemann; Magnus Bender; Özgür L. Özçep; Nele Russwinkel; Kai Sauerwald; Diedrich Wolter (Hrsg.). Proceedings of the Joint Workshop on Humanities-Centred Artificial Intelligence and Formal & Cognitive Reasoning co-located with 48th German Conference on Artificial Intelligence. Joint Workshop on Humanities-Centred Artificial Intelligence and Formal & Cognitive Reasoning (CHAI and FCR-2025), located at 48th German Conference on Artificial Intelligence (KI-2025), September 16-19, Potsdam, Germany, Pages 41-56, Vol. 4058, CEUR, 10/2025.

  3. Khang Nguyen; An T. Le; Tien Pham; Manfred Huber; Jan Peters; Minh Nhat Vu

    FlowMP: Learning Motion Fields for Robot Planning with Conditional Flow Matching

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2503.06135, Pages 1-7, arXiv, 2025.

  4. Théo Vincent; Tim Lukas Faust; Yogesh Tripathi; Jan Peters; Carlo D'Eramo

    Eau De emphQ-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2503.01437, Pages 1-26, arXiv, 2025.

  5. Nico Bohlinger; Jan Peters

    Massively Scaling Explicit Policy-conditioned Value Functions

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2502.11949, Pages 1-5, arXiv, 2025.

  6. Daniel Palenicek; Florian Vogt; Jan Peters

    Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2502.07523, Pages 1-23, arXiv, 2025.

  7. Fabian Roth; Dominik K. Klein; Maximilian Kannapinn; Jan Peters; Oliver Weeger

    Stable Port-Hamiltonian Neural Networks

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2502.02480, Pages 1-15, arXiv, 2025.

  8. Onur Celik; Zechu Li; Denis Blessing; Ge Li; Daniel Palanicek; Jan Peters; Georgia Chalvatzaki; Gerhard Neumann

    DIME:Diffusion-Based Maximum Entropy Reinforcement Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2502.02316, Pages 1-20, arXiv, 2025.

  9. Anish Abhijit Diwan; Julen Urain; Jens Kober; Jan Peters

    Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2501.14856, Pages 1-22, arXiv, 2025.

  10. Leonhard Keller; Daniel Tanneberg; Jan Peters

    Neuro-Symbolic Imitation Learning: Discovering Symbolic Abstractions for Skill Learning

    In: IEEE International Conference on Robotics and Automation, ICRA 2025, Atlanta, GA, USA, May 19-23, 2025. IEEE International Conference on Robotics and Automation (ICRA), Pages 6519-6526, IEEE, 2025.

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