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Publications

Displaying results 161 to 170 of 675.
  1. ExPrIS: Knowledge-Level Expectations as Priors for Object Interpretation from Sensor Data

    In: Lars Kunze (Hrsg.). KI - Künstliche Intelligenz, German Journal on Artificial Intelligence - Organ des Fachbereiches "Künstliche Intelligenz" der Gesellschaft für Informatik e.V. (KI), Springer Nature, 2026.

  2. Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2310.06549, Pages 1-31, arXiv, 2023.

  3. Quentin Delfosse; Wolfgang Stammer; Thomas Rothenbacher; Dwarak Vittal; Kristian Kersting

    Boosting Object Representation Learning via Motion and Object Continuity

    In: Danai Koutra; Claudia Plant; Manuel Gomez Rodriguez; Elena Baralis; Francesco Bonchi (Hrsg.). Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part IV. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Pages 610-628, Lecture Notes in Computer Science, Vol. 14172, Springer, 2023.

  4. Jannis Blüml; Johannes Czech; Kristian Kersting

    AlphaZe(_ast)(_ast): AlphaZero-like baselines for imperfect information games are surprisingly strong

    In: Frontiers in Artificial Intelligence, Vol. 6, Pages 1-18, Frontiers, 2023.

  5. Frieder Uhlig; Lukas Struppek; Dominik Hintersdorf; Thomas Göbel; Harald Baier; Kristian Kersting

    Combining AI and AM - Improving approximate matching through transformer networks

    In: Digital Investigation, Vol. 45, No. Supplement, Pages 1-13, arXiv, 2023.

  6. Shange Wang; Lin Xu; Linshuai Zhang; Yujie Zhang; Chen Li; Marcin Grzegorzek; Jing Guo; Tao Jiang

    HHBSNet: a global channel–spatial attention and multi-scale dilated convolution network for automatic melasma segmentation

    In: Frontiers in Physiology, Vol. 16 - 2025, Frontiers Media SA, 11/2025.

  7. Leonid Schwenke; Till Stückemann; Martin Atzmueller

    Evaluating Higher-Level and Symbolic Features in Deep Learning on Time Series: Towards Simpler Explainability

    In: Proc. International Work-Conference on Artificial Neural Networks. International Work-Conference on Artificial Neural Networks (IWANN), Springer, 2025.

  8. Harihara Bharathy Swaminathan; Aron Sommer; Uri Iurgel; Andreas Becker; Martin Atzmueller

    Comparative Analysis of Deep Learning-Based Feature Extractors for Change Detection in Automotive Radar Maps

    In: IEEE Access (IEEE), Vol. 13, Pages 130629-130637, IEEE, 2025.

  9. Roman Heinrich; Oleksandr Havrylov; Manisha Luthra; Johannes Wehrstein; Carsten Binnig

    Opening The Black-Box: Explaining Learned Cost Models For Databases

    In: Proceedings of the VLDB Endowment (PVLDB), Vol. 18, No. 12, Pages 5255-5258, arXiv, 2025.

  10. Joao Carvalho; An T. Le; Philipp Jahr; Qiao Sun; Julen Urain; Dorothea Koert; Jan Peters

    Grasp Diffusion Network: Learning Grasp Generators from Partial Point Clouds with Diffusion Models in SO(3)xR3

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2412.08398, Pages 1-8, arXiv, 2024.