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Publications

Displaying results 161 to 170 of 668.

  1. Marian Renz; Martin Günther; Felix Igelbrink; Oscar Lima; Martin Atzmueller

    ExPrIS: Knowledge-Level Expectations as Priors for Object Interpretation from Sensor Data

    In: Lars Kunze (Hrsg.). KI - Künstliche Intelligenz, German Journal on Artificial Intelligence - Organ des Fachbereiches "Künstliche Intelligenz" der Gesellschaft für Informatik e.V. (KI), Springer Nature, 2026.

  2. Théo Vincent; Yogesh Tripathi; Tim Lukas Faust; Yaniv Oren; Jan Peters; Carlo D'Eramo

    Bridging the Performance Gap Between Target-Free and Target-Based Reinforcement Learning With Iterated Q-Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2506.04398, Pages 1-22, arXiv, 2025.

  3. 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.

  4. 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.

  5. 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.

  6. Claudius Kienle; Benjamin Alt; Darko Katic; Rainer Jäkel; Jan Peters

    QueryCAD: Grounded Question Answering for CAD Models

    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 5798-5805, IEEE, 2025.

  7. Théo Vincent; Daniel Palenicek; Boris Belousov; Jan Peters; Carlo D'Eramo

    Iterated emphQ-Network: Beyond One-Step Bellman Updates in Deep Reinforcement Learning

    In: Transactions on Machine Learning Research (TMLR), Vol. 2025, Pages 1-26, arXiv, 2025.

  8. Carlos E. Luis; Alessandro G. Bottero; Julia Vinogradska; Felix Berkenkamp; Jan Peters

    Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning under Partial Observability

    In: Transactions on Machine Learning Research (TMLR), Vol. 2025, Pages 1-31, arXiv, 2025.

  9. Hector Kohler; Quentin Delfosse; Riad Akrour; Kristian Kersting; Philippe Preux

    Interpretable and Editable Programmatic Tree Policies for Reinforcement Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2405.14956, Pages 1-27, arXiv, 2024.

  10. Michael Poli; Armin W. Thomas; Eric Nguyen; Pragaash Ponnusamy; Björn Deiseroth; Kristian Kersting; Taiji Suzuki; Brian L. Hie; Stefano Ermon; Christopher Ré; Ce Zhang; Stefano Massaroli

    Mechanistic Design and Scaling of Hybrid Architectures

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2403.17844, Pages 1-34, arXiv, 2024.

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