Skip to main content Skip to main navigation

Publications

Displaying results 281 to 290 of 646.
  1. 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.

  2. 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.

  3. Philip Becker-Ehmck; Maximilian Karl; Jan Peters; Patrick van der Smagt

    Learning to Fly via Deep Model-Based Reinforcement Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2003.08876, Pages 0-10, arXiv, 2020.

  4. Marcus Ebner von Eschenbach; Binyamin Manela; Jan Peters; Armin Biess

    Metric-Based Imitation Learning Between Two Dissimilar Anthropomorphic Robotic Arms

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2003.02638, Pages 0-10, arXiv, 2020.

  5. 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.

  6. Quentin Delfosse; Jannis Blüml; Bjarne Gregori; Sebastian Sztwiertnia; Kristian Kersting

    OCAtari: Object-Centric Atari 2600 Reinforcement Learning Environments

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2306.08649, Pages 0-10, arXiv, 2023.

  7. Lukas Helff; Wolfgang Stammer; Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting

    V-LoL: A Diagnostic Dataset for Visual Logical Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2306.07743, Pages 0-10, arXiv, 2023.

  8. Steven Braun; Martin Mundt; Kristian Kersting

    Deep Classifier Mimicry without Data Access

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2306.02090, Pages 0-10, arXiv, 2023.

  9. 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.