Skip to main content Skip to main navigation

Publications

Displaying results 371 to 380 of 682.
  1. Riad Akrour; Filipe Veiga; Jan Peters; Gerhard Neumann

    Regularizing Reinforcement Learning with State Abstraction

    In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2018), October 1-5, Madrid, Spain, Pages 534-539, IEEE, 2018.

  2. Paavo Parmas; Carl Edward Rasmussen; Jan Peters; Kenji Doya

    PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos

    In: Jennifer G. Dy; Andreas Krause (Hrsg.). Proceedings of the 35th International Conference on Machine Learning. International Conference on Machine Learning (ICML-2018), July 10-15, Stockholm, Sweden, Pages 4062-4071, Proceedings of Machine Learning Research, Vol. 80, PMLR, 2018.

  3. Pascal Klink; Carlo D'Eramo; Jan Peters; Joni Pajarinen

    Self-Paced Deep Reinforcement Learning

    In: Hugo Larochelle; Marc'Aurelio Ranzato; Raia Hadsell; Maria-Florina Balcan; Hsuan-Tien Lin (Hrsg.). Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020. Neural Information Processing Systems (NeurIPS-2020), December 6-12, Curran Associates, Inc. 2020.

  4. Melvin Laux; Oleg Arenz; Jan Peters; Joni Pajarinen

    Deep Adversarial Reinforcement Learning for Object Disentangling

    In: IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2020), October 24 - January 24, Las Vegas, NV, USA, Pages 5504-5510, IEEE, 2020.

  5. Julen Urain; Michele Ginesi; Davide Tateo; Jan Peters

    ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows

    In: IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2020), October 24 - January 24, Las Vegas, NV, USA, Pages 5231-5237, IEEE, 2020.

  6. Carlo D'Eramo; Davide Tateo; Andrea Bonarini; Marcello Restelli; Jan Peters

    Sharing Knowledge in Multi-Task Deep Reinforcement Learning

    In: 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. International Conference on Learning Representations (ICLR), OpenReview.net, 2020.

  7. Sebastián Gómez-González; Sergey Prokudin; Bernhard Schölkopf; Jan Peters

    Real Time Trajectory Prediction Using Deep Conditional Generative Models

    In: IEEE Robotics and Automation Letters (RA-L), Vol. 5, No. 2, Pages 970-976, IEEE, 2020.

  8. Julien Brosseit; Benedikt Hahner; Fabio Muratore; Michael Gienger; Jan Peters

    Distilled Domain Randomization

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2112.03149, Pages 0-10, arXiv, 2021.

  9. Antoine Grosnit; Rasul Tutunov; Alexandre Max Maraval; Ryan-Rhys Griffiths; Alexander I. Cowen-Rivers; Lin Yang; Lin Zhu; Wenlong Lyu; Zhitang Chen; Jun Wang; Jan Peters; Haitham Bou-Ammar

    High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2106.03609, Pages 0-10, arXiv, 2021.

  10. 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.