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Publications

Displaying results 51 to 60 of 563.

  1. Riad Akrour; Asma Atamna; Jan Peters

    Convex optimization with an interpolation-based projection and its application to deep learning

    In: Machine Learning, Vol. 110, No. 8, Pages 2267-2289, Springer, 2021.

  2. Carlo D'Eramo; Andrea Cini; Alessandro Nuara; Matteo Pirotta; Cesare Alippi; Jan Peters; Marcello Restelli

    Gaussian Approximation for Bias Reduction in Q-Learning

    In: Journal of Machine Learning Research, Vol. 22, Pages 277:1-277:51, JMLR, 2021.

  3. Niyati Rawal; Dorothea Koert; Cigdem Turan; Kristian Kersting; Jan Peters; Ruth Stock-Homburg

    ExGenNet: Learning to Generate Robotic Facial Expression Using Facial Expression Recognition

    In: Frontiers in Robotics and AI, Vol. 8, Pages 0-10, Frontiers, 2021.

  4. Bang You; Jingming Xie; Youping Chen; Jan Peters; Oleg Arenz

    Self-supervised Sequential Information Bottleneck for Robust Exploration in Deep Reinforcement Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2209.05333, Pages 0-10, arXiv, 2022.

  5. Tuan Dam; Carlo D'Eramo; Jan Peters; Joni Pajarinen

    A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2202.07071, Pages 0-10, arXiv, 2022.

  6. Vignesh Prasad; Dorothea Koert; Ruth Stock-Homburg; Jan Peters; Georgia Chalvatzaki

    MILD: Multimodal Interactive Latent Dynamics for Learning Human-Robot Interaction

    In: 21st IEEE-RAS International Conference on Humanoid Robots. IEEE-RAS International Conference on Humanoid Robots (Humanoids-2022), November 28-30, Ginowan, Japan, Pages 472-479, IEEE, 2022.

  7. Riad Akrour; Davide Tateo; Jan Peters

    Continuous Action Reinforcement Learning From a Mixture of Interpretable Experts

    In: IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 44, No. 10, Pages 6795-6806, IEEE, 2022.

  8. Michael Lutter; Christian Ritter; Jan Peters

    Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning

    In: 7th International Conference on Learning Representations. International Conference on Learning Representations (ICLR-2019), May 6-9, New Orleans, LA, USA, OpenReview.net, 2019.

  9. Riad Akrour; Davide Tateo; Jan Peters

    Reinforcement Learning from a Mixture of Interpretable Experts

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2006.05911, Pages 0-10, arXiv, 2020.

  10. Andrea Cini; Carlo D'Eramo; Jan Peters; Cesare Alippi

    Deep Reinforcement Learning with Weighted Q-Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2003.09280, Pages 0-10, arXiv, 2020.

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