Elmar Rückert

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Research output

  1. Published

    Exploiting Chlorophyll Fluorescense for building robust low-cost Mowing Area Detectors

    Rottmann, N., Bruder, R., Schweikard, A. & Rueckert, E., 25 Oct 2020.

    Research output: Contribution to conference › Paper › peer-review

  2. Published

    Extracting low-dimensional control variables for movement primitives

    Rueckert, E., Mundo, J., Paraschos, A., Peters, J. & Neumann, G., 29 Jun 2015, In: Proceedings / IEEE International Conference on Robotics and Automation. 2015-June, June, p. 1511-1518 8 p., 7139390.

    Research output: Contribution to journal › Conference article › peer-review

  3. Published

    Green and blue infrastructure as model system for emissions of technology-critical elements

    Trimmel, S., Spörl, P., Haluza, D., Lashin, N., Meisel, T. C., Pitha, U., Prohaska, T., Puschenreiter, M., Rückert, E., Spangl, B., Wiedenhofer, D. & Irrgeher, J., 20 May 2024, In: Science of the total environment. 934.2024, 15, 15 p., 173364.

    Research output: Contribution to journal › Article › Research › peer-review

  4. Published

    Integrating Human Expertise in Continuous Spaces: A Novel Interactive Bayesian Optimization Framework with Preference Expected Improvement

    Feith, N. & Rückert, E., 1 Mar 2024, In: IEEE International Conference on Ubiquitous Robots.

    Research output: Contribution to journal › Conference article › peer-review

  5. Published

    Interactive Human–Robot Skill Transfer: A Review of Learning Methods and User Experience

    Cansev, M. E., Xue, H., Rottmann, N., Bliek, A., Miller, L. E., Rückert, E. & Beckerle, P., 6 May 2021, In: Advanced Intelligent Systems. 3.2021, 7, 11 p., 2000247.

    Research output: Contribution to journal › Article › Research › peer-review

  6. Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks

    Tanneberg, D., Peters, J. & Rueckert, E., Jan 2019, In: Neural networks. 109.2019, January, p. 67-80 14 p.

    Research output: Contribution to journal › Article › Research › peer-review

  7. Inverse reinforcement learning via nonparametric spatio-temporal subgoal modeling

    Šošić, A., Rueckert, E., Peters, J., Zoubir, A. M. & Koeppl, H., 1 Oct 2018, In: Journal of Machine Learning Research. 19.2018, 69, 45 p.

    Research output: Contribution to journal › Article › Research › peer-review

  8. Published

    KI 2021: Advances in Artificial Intelligence - Preface

    Edelkamp, S., Möller, R. & Rückert, E., 2021, KI 2021: Advances in Artificial Intelligence: 44th German Conference on AI, Virtual Event, September 27 – October 1, 2021, Proceedings. Edelkamp, S., Möller, R. & Rückert, E. (eds.). Vol. 12873 LNAI. p. v-vi (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  9. Published

    KIRAMET: AI-based Recycling of Metal Composite Waste

    Neubauer, M. & Rückert, E., 6 Jun 2024.

    Research output: Contribution to conference › Poster › Research

  10. Learned graphical models for probabilistic planning provide a new class of movement primitives

    Rückert, E. A., Neumann, G., Toussaint, M. & Maass, W., 2 Jan 2013, (E-pub ahead of print) In: Frontiers in computational neuroscience. 6.2013, January, 20 p., 97.

    Research output: Contribution to journal › Article › Research › peer-review

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