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Publications

Displaying results 351 to 360 of 681.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  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. Dinh Nam Pham; Vera Czehmann; Eleftherios Avramidis

    Disambiguating Signs: Deep Learning-based Gloss-level Classification for German Sign Language by Utilizing Mouth Actions

    In: Proceedings of the 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN-2023), October 4-6, Bruges, Belgium, ISBN 978-2-87587-088-9. i6doc.com publ. 10/2023.

  8. Amos Smith; Jeremy Coffelt; Kai Lingemann

    A Deep Learning Framework for Semantic Segmentation of Underwater Environments

    In: OCEANS 22 Hampton Roads. OCEANS MTS/IEEE Conference (OCEANS-2022), October 17-20, Hampton Roads, VA, USA, IEEE, 10/2022.

  9. Michael Lutter; Boris Belousov; Kim Listmann; Debora Clever; Jan Peters

    HJB optimal feedback control with deep differential value functions and action constraints

    In: Leslie Pack Kaelbling; Danica Kragic; Komei Sugiura (Hrsg.). 3rd Annual Conference on Robot Learning. Conference on Robot Learning (CoRL-2019), October 30 - November 1, Osaka, Japan, Pages 640-650, Proceedings of Machine Learning Research (PMLR), Vol. 100, PMLR, 2019.

  10. Michael Lutter; Debora Clever; Boris Belousov; Kim Listmann; Jan Peters

    Evaluating the Robustness of HJB Optimal Feedback Control

    In: International Symposium on Robotics. International Symposium on Robotics (ISR-2020), 52th, December 9-10, Pages 1-8, VDE, 2020.

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