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Publications

Displaying results 311 to 320 of 682.

  1. Sk Aziz Ali; Djamila Aouada; Gerd Reis; Didier Stricker (Hrsg.)

    DELO: Deep Evidential LiDAR Odometry using Partial Optimal Transport

    International Conference on Computer Vision (ICCV-2023), 2023.

  2. Daniel Tanneberg; Alexandros Paraschos; Jan Peters; Elmar Rueckert

    Deep spiking networks for model-based planning in humanoids

    In: 16th IEEE-RAS International Conference on Humanoid Robots. IEEE-RAS International Conference on Humanoid Robots (Humanoids-2016), November 15-17, Cancun, Mexico, Pages 656-661, IEEE, 2016.

  3. Simone Parisi; Simon Ramstedt; Jan Peters

    Goal-driven dimensionality reduction for reinforcement learning

    In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2017), September 24-28, Vancouver, BC, Canada, Pages 4634-4639, IEEE, 2017.

  4. Hany Abdulsamad; Oleg Arenz; Jan Peters; Gerhard Neumann

    State-Regularized Policy Search for Linearized Dynamical Systems

    In: Laura Barbulescu; Jeremy Frank; Mausam; Stephen F. Smith (Hrsg.). Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling. International Conference on Automated Planning and Scheduling (ICAPS-2017), June 18-23, Pittsburgh, Pennsylvania, USA, Pages 419-424, AAAI Press, 2017.

  5. Sahil Sidheekh; Kristian Kersting; Sriraam Natarajan

    Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference

    In: Robin J. Evans; Ilya Shpitser (Hrsg.). Uncertainty in Artificial Intelligence. Conference in Uncertainty in Artificial Intelligence (UAI), July 31 - August 4, Pittsburgh, PA, USA, Pages 1964-1973, Proceedings of Machine Learning Research, Vol. 216, PMLR, 2023.

  6. Hikaru Shindo; Viktor Pfanschilling; Devendra Singh Dhami; Kristian Kersting

    (alpha)ILP: thinking visual scenes as differentiable logic programs

    In: Machine Learning, Vol. 112, No. 5, Pages 1465-1497, Springer, 2023.

  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. Jason Raphael Rambach; Bruno Mirbach; Yuriy Anisimov; Didier Stricker

    Time-of-Flight Depth Sensing for Automotive Safety and Smart Building Applications: The VIZTA Project

    In: IEEE Access (IEEE), Vol. 11, Pages 105819-105829, IEEE, 10/2023.

  10. David Steinmann; Wolfgang Stammer; Felix Friedrich; Kristian Kersting

    Learning to Intervene on Concept Bottlenecks

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2308.13453, Pages 0-10, arXiv, 2023.

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