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Publications

Displaying results 301 to 310 of 666.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Michael Lutter; Kim Listmann; Jan Peters

    Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems

    In: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2019), November 3-8, Macau, China, Pages 7718-7725, IEEE, 2019.

  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. Babu Ajish; Frank Kirchner

    Terrain Adaption Controller for a Walking Excavator Robot using Deep Reinforcement Learning

    In: 2021 20th International Conference on Advanced Robotics (ICAR). International Conference On Advanced Robotics (ICAR-2021), December 7-10, Ljubljana, Slovenia, Pages 64-70, IEEE Xplore, ieeexplore.ieee.org/document/9659399, 12/2021.

  10. Jens Popper; Carsten Harms; Martin Ruskowski

    Enabling reliable Visual Quality Control in Smart Factories through TSN

    In: Roberto Teti; Doriana M. D'Addona (Hrsg.). Procedia CIRP, Vol. 88 - 13th CIRP Conference on Intelligent Computation in Manufacturing Engineering, 17-19 July 2019, Gulf of Naples, Italy, Pages 549-553, Elsevier B.V. 2020.

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