Skip to main content Skip to main navigation

Publikationen

Zeige Ergebnisse 1511 bis 1520 von 2315.

  1. Timo P. Gros; Nicola Müller; Daniel Höller; Verena Wolf

    Safe Reinforcement Learning Through Regret and State Restorations in Evaluation Stages

    In: Workshop on Reliable Data-Driven Planning and Scheduling. International Conference on Automated Planning and Scheduling (ICAPS-2024), Springer, 2024.

  2. Bernd Finkbeiner; Felix Jahn; Julian Siber

    Counterfactual Explanations for MITL Violations

    In: Siddharth Barman; Slawomir Lasota (Hrsg.). 44th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2024). IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS-2024), December 16-18, Pages 22:1-22:25, Leibniz International Proceedings in Informatics (LIPIcs), Vol. 323, ISBN 978-3-95977-355-3, Schloss Dagstuhl -- Leibniz-Zentrum für Informatik, Dagstuhl, Germany, 12/2024.

  3. Joshua Meyer; Alexander Rath; Ömercan Yazici; Philipp Slusallek

    MARS: Multi-sample Allocation through Russian roulette and Splitting

    In: SIGGRAPH Asia 2024 Conference Papers. ACM SiggraphAsia (SigAsia-2024), December 3-6, Tokyo, Japan, SA '24 (SA '24), ISBN 9798400711312, Association for Computing Machinery, New York, NY, USA, 12/2024.

  4. Tobias Stollenwerk; Somtapa Bhattacharya; Michele Cattelan; Alessandro Ciani; Gabriele Compostella; David Headley; Johannes Klepsch; Matthias Klusch; Markus Leder; Antonio Macaluso; Kristel Michielsen; Dmytro Nabok; Anestis Papanikolaou; Alexander Rausch; Marco Schumann; Andrea Skolik; Sheir Yarkoni; Frank K. Wilhelm

    Q(AI)2: Quantum Artificial Intelligence for the Automotive Industry

    In: Matthias Klusch; Jörg Lässig; Frank Wilhelm (Hrsg.). KI - Künstliche Intelligenz, German Journal on Artificial Intelligence - Organ des Fachbereiches "Künstliche Intelligenz" der Gesellschaft für Informatik e.V. (KI), Vol. 4/24, Pages 1-9, Springer, 2024.

  5. Philippe Weier; Alexander Rath; Élie Michel; Iliyan Georgiev; Philipp Slusallek; Tamy Boubekeur

    N-BVH: Neural ray queries with bounding volume hierarchies

    In: Andres Burbano; Denis Zorin; Wojciech Jarosz (Hrsg.). Proceedings - SIGGRAPH 2024 Conference Papers. ACM Siggraph (Siggraph-24), July 27 - August 1, Denver, CO, USA, Pages 1-11, Vol. 25, ISBN 979-8-4007-0525-0, Association for Computing Machinery, New York, NY, USA, 7/2024.

  6. Tuan Dam; Carlo D'Eramo; Jan Peters; Joni Pajarinen

    A unified perspective on value backup and exploration in monte-carlo tree search

    In: Journal of Artificial Intelligence Research (JAIR), Vol. 81, Pages 511-577, 2024.

  7. Liane Vogel; Jan-Micha Bodensohn; Carsten Binnig

    WikiDBs: A Large-Scale Corpus Of Relational Databases From Wikidata

    In: A. Globerson; L. Mackey; D. Belgrave; A. Fan; U. Paquet; J. Tomczak; C. Zhang (Hrsg.). Advances in Neural Information Processing Systems. Neural Information Processing Systems (NeurIPS), Pages 41186-41201, Vol. 37, Curran Associates, Inc. 2024.

  8. 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.

  9. 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.

  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.

Jahr

Mehr Optionen