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Publikationen

Zeige Ergebnisse 781 bis 790 von 13864.

  1. Hoai-Chau Tran; Ho Minh Duy Nguyen; Manh-Duy Nguyen; Ngan Hoang Le; Binh T. Nguyen

    Energy Minimizing-based Token Merging for Accelerating Transformers

    In: International Conference on Learning Representations (ICLR), Practical ML for Low Resource Settings Workshop. International Conference on Learning Representations (ICLR), May 11-12, JMLR.org, 2024.

  2. Ho Minh Duy Nguyen; Nina Lukashina; Tai Nguyen; An T. Le; TrungTin Nguyen; Nhat Ho; Jan Peters; Daniel Sonntag; Viktor Zaverkin; Mathias Niepert

    Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks

    In: Proceedings of the 41st International Conference on Machine Learning. International Conference on Machine Learning (ICML), July 21-27, Austria, JMLR.org, 2024.

  3. Lawrence Benson; Carsten Binnig; Jan-Micha Bodensohn; Federico Lorenzi; Jigao Luo; Danica Porobic; Tilmann Rabl; Anupam Sanghi; Russell Sears; Pinar Tözün; Tobias Ziegler

    Surprise Benchmarking: The Why, What, and How

    In: Proceedings of the Tenth International Workshop on Testing Database Systems, DBTest 2024, Santiago, Chile, 9 June 2024. International Workshop on Testing Database Systems (DBTest), Pages 1-8, ACM, 2024.

  4. Jan-Micha Bodensohn; Ulf Brackmann; Liane Vogel; Anupam Sanghi; Carsten Binnig

    Automating Enterprise Data Engineering with LLMs

    In: NeurIPS 2024 Third Table Representation Learning Workshop. Table Representation Learning Workshop (TRL), located at NeurIPS 2024, December 14, NeurIPS, 2024.

  5. Benjamin Blumhofer; Jonas Weigand; Leonhard Kunz; Pascal Rübel; Achim Wagner

    Detection of Rare Fault Cases for Mobile Robot Applications

    In: Achim Wagner; Kosmas Alexopoulos; Sotiris Makris (Hrsg.). Advances in Artificial Intelligence in Manufacturing. European Symposium on Artificial Intelligence in Manufacturing (ESAIM-2023), Cham, Pages 61-70, ISBN 978-3-031-57496-2, Springer Nature Switzerland, 2024.

  6. Jibinraj Antony; Dorotea Jalu¨ić; Simon Bergweiler; Ákos Hajnal; Veronika ´labravec; Márk Emődi; Dejan Strbad; Tatjana Legler; Attila Csaba Marosi

    Adapting to Changes: A Novel Framework for Continual Machine Learning in Industrial Applications

    In: Journal of Grid Computing, Vol. 22 (71), Pages 1-19, Springer, 11/2024.

  7. Jibinraj Antony; Vinit Vikas Hegiste; Ali Nazeri; Hooman Tavakoli Ghinani; Snehal Walunj; Christiane Plociennik; Martin Ruskowski

    Enhancing Object Detection Performance for Small Objects Through Synthetic Data Generation and Proportional Class-Balancing Technique: A Comparative Study in Industrial Scenarios

    In: Achim Wagner; Kosmas Alexopoulos; Sotiris Makris (Hrsg.). Advances in Artificial Intelligence in Manufacturing. European Symposium on Artificial Intelligence in Manufacturing (ESAIM-2023), Cham, Pages 90-105, ISBN 978-3-031-57496-2, Springer Nature Switzerland, 2024.

  8. Sofija Engelson; Jan Ehrhardt; Timo Kepp; Joshua Niemeijer; Heinz Handels

    LNQ Challenge 2023: Learning Mediastinal Lymph Node Segmentation with a Probabilistic Lymph Node Atlas

    In: Steve Pieper; Erik Ziegler; Tawa Idris; Bhanusupriya Somarouthu; Reuben Dorent; Gordon Harris; Ron Kikinis (Hrsg.). Machine Learning for Biomedical Imaging (MELBA), Vol. 2, No. MICCAI 2023 LNQ challenge special issue, Pages 817-833, MELBA Journal, 5/2024.

  9. Jana-Rebecca Rehse; Sander J. J. Leemans; Peter Fettke; Jan Martijn E. M. van der Werf

    On Process Discovery Experimentation: Addressing the Need for Research Methodology in Process Discovery

    In: ACM Transactions on Software Engineering and Methodology (TOSEM), Vol. 34, No. 1, Article No.: 3, Pages 1-29, Association for Computing Machinery, New York, 2024.

  10. Jan-Micha Bodensohn; Ulf Brackmann; Liane Vogel; Matthias Urban; Anupam Sanghi; Carsten Binnig

    LLMs for Data Engineering on Enterprise Data

    In: Proceedings of Workshops at the 50th International Conference on Very Large Data Bases, VLDB 2024. International Workshop on Tabular Data Analysis (TaDA), VLDB.org, 2024.

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