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Publikationen

Zeige Ergebnisse 1731 bis 1740 von 13867.

  1. Tobias Baumgartner; Benjamin Paaßen; Stefanie Klatt

    Extracting spatial knowledge from track and field broadcasts for monocular 3D human pose estimation

    In: nature scientific reports (Sci Rep), Vol. 13, No. 14031, Pages 1-11, Springer nature, 2023.

  2. Fabian Maas genannt Bermpohl; Andreas Bresser; Malte Langosz

    Experimental Evaluation of AGV Dispatching Methods in an Agent-Based Simulation Environment and a Digital Twin

    In: Applied Sciences, Vol. 13, No. 10, Pages 1-32, MDPI, 5/2023.

  3. Benjamin Hülsen; Niklas A. Mulsow; Adam Dabrowski; Wiebke Brinkmann; Joel Gützlaff; Leon Spies; Markus Czupalla; Frank Kirchner

    Towards an Autonomous Micro Rover with Night Survivability for Lunar Exploration

    In: 74th International Astronautical Congress 2023. International Astronautical Congress (IAC-2023), October 2-6, Baku, Azerbaijan, International Astronautical Federation (IAF), 10/2023.

  4. Sophie F. Jentzsch; Kristian Kersting

    ChatGPT is fun, but it is not funny! Humor is still challenging Large Language Models

    In: Jeremy Barnes; Orphée De Clercq; Roman Klinger (Hrsg.). Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis. Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA), July 14, Toronto, Canada, Pages 325-340, Association for Computational Linguistics, 2023.

  5. Fabrizio Ventola; Steven Braun; Zhongjie Yu; Martin Mundt; Kristian Kersting

    Probabilistic circuits that know what they don't know

    In: Robin J. Evans; Ilya Shpitser (Hrsg.). Uncertainty in Artificial Intelligence, UAI 2023, July 31 - 4 August 2023, Pittsburgh, PA, USA. Conference in Uncertainty in Artificial Intelligence (UAI), Pages 2157-2167, Proceedings of Machine Learning Research, Vol. 216, PMLR, 2023.

  6. 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.

  7. Jingyuan Sha; Hikaru Shindo; Kristian Kersting; Devendra Singh Dhami

    Neural-Symbolic Predicate Invention: Learning Relational Concepts from Visual Scenes

    In: Artur S. d'Avila Garcez; Tarek R. Besold; Marco Gori; Ernesto Jiménez-Ruiz (Hrsg.). Proceedings of the 17th International Workshop on Neural-Symbolic Learning and Reasoning. International Workshop on Neural-Symbolic Learning and Reasoning (NeSy), July 3-5, Italy, Pages 103-117, CEUR Workshop Proceedings, Vol. 3432, CEUR-WS.org, 2023.

  8. Arseny Skryagin; Daniel Ochs; Devendra Singh Dhami; Kristian Kersting

    Scalable Neural-Probabilistic Answer Set Programming

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2306.08397, Pages 0-10, arXiv, 2023.

  9. 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.

  10. Subarnaduti Paul; Lars-Joel Frey; Roshni Kamath; Kristian Kersting; Martin Mundt

    Masked Autoencoders are Efficient Continual Federated Learners

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2306.03542, Pages 0-10, arXiv, 2023.

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