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Publications

Displaying results 1771 to 1780 of 15084.

  1. Jan-Micha Bodensohn; Carsten Binnig

    Rethinking Table Retrieval from Data Lakes

    In: Proceedings of the Seventh International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, aiDM 2024, Santiago, Chile, 14 June 2024. International Workshop on Exploiting Artificial Intelligence Techniques for Data Management (aiDM), Pages 2:1-2:5, ACM, 2024.

  2. Matthias Urban; Carsten Binnig

    ELEET: Efficient Learned Query Execution over Text and Tables

    In: Proceedings of the VLDB Endowment (PVLDB), Vol. 17, No. 13, Pages 4867-4880, VLDB, 2024.

  3. Eduardo Souza dos Reis; Mohamed Abdelaal; Carsten Binnig

    Generalizable Data Cleaning of Tabular Data in Latent Space

    In: Proceedings of the VLDB Endowment (PVLDB), Vol. 17, No. 13, Pages 4786-4798, VLDP, 2024.

  4. 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.

  5. Maximilian Tölle; Theo Gruner; Daniel Palenicek; Jonas Günster; Puze Liu; Joe Watson; Davide Tateo; Jan Peters

    Towards Safe Robot Foundation Models

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2503.07404, Pages 1-3, arXiv, 2025.

  6. Mathias Trampler; Marc Tabie; Julia Habenischt; Elsa Andrea Kirchner

    Exoskeleton based microgravity simulation for astronaut training

    In: MDPI Engineering Proceedings (E-ISSN 2673-4591). EASN International Conference on Innovation in Aviation & Space towards Sustainability Today & Tomorrow (EASN-2025), 15th, October 14-17, Madrid, Spain, MDPI, 2026.

  7. Khang Nguyen; An T. Le; Tien Pham; Manfred Huber; Jan Peters; Minh Nhat Vu

    FlowMP: Learning Motion Fields for Robot Planning with Conditional Flow Matching

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2503.06135, Pages 1-7, arXiv, 2025.

  8. Théo Vincent; Tim Lukas Faust; Yogesh Tripathi; Jan Peters; Carlo D'Eramo

    Eau De emphQ-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2503.01437, Pages 1-26, arXiv, 2025.

  9. Nico Bohlinger; Jan Peters

    Massively Scaling Explicit Policy-conditioned Value Functions

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2502.11949, Pages 1-5, arXiv, 2025.

  10. Daniel Palenicek; Florian Vogt; Jan Peters

    Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2502.07523, Pages 1-23, arXiv, 2025.

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