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Publications

Displaying results 271 to 280 of 682.

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

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

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2507.14495, Pages 1-4, arXiv, 2025.

  2. Sara Narteni; Alberto Carlevaro; Zeming Duan; Serge Autexier; Maurizio Mongelli

    Physics-Aware Conformal Prediction for Deep Learning-based Wheelchair Local Navigation

    In: Khuong An Nguyen; Zhiyuan Luo; Harris Papadopoulos; Tuwe Löfström; Lars Carlsson; Henrik Boström (Hrsg.). Fourteenth Symposium on Conformal and Probabilistic Prediction with Applications. Symposium in Conformal and Probabilistic Prediction with Applications (COPA-2025), September 10-12, London, United Kingdom, Pages 778-780, Proceedings of Machine Learning Research (PMLR), Vol. 266, PMLR, 9/2025.

  3. Sumantrak Mukherjee; Mouad Elhamdi; George Mohler; David Antony Selby; Yao Xie; Sebastian Vollmer; Gerrit Großmann

    Neural Spatiotemporal Point Processes: Trends and Challenges

    In: Transactions on Machine Learning Research (TMLR), Vol. NA, Pages 1-27, JMLR, 11/2025.

  4. Lukas Struppek; Dominik Hintersdorf; Kristian Kersting

    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.

  5. 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.

  6. 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.

  7. 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.

  8. Max Bramer; Frederic Theodor Stahl (Hrsg.)

    Artificial Intelligence XLII

    SGAI International Conference on Artificial Intelligence (AI-2025), 45th SGAI International Conference on Artificial Intelligence, December 16-18, Cambridge, United Kingdom, Lecture Notes in Computer Science (LNAI), Vol. 16302, Springer Nature Switzerland, Cham, 12/2025.

  9. Max Bramer; Frederic Theodor Stahl (Hrsg.)

    Artificial Intelligence XLII

    SGAI International Conference on Artificial Intelligence (AI-2025), 45th SGAI International Conference on Artificial Intelligence, December 16-18, Cambridge, United Kingdom, Lecture Notes in Computer Science (LNAI), Vol. 16301, Springer Nature Switzerland, Cham, 12/2025.

  10. Marian Renz; Martin Günther; Felix Igelbrink; Oscar Lima; Martin Atzmueller

    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.

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