Skip to main content Skip to main navigation

Publications

Displaying results 191 to 200 of 661.
  1. Busra Sebin; Nazim Taskin; Nijat Mehdiyev

    Exploring the Intersection of Large Language Models (LLMs) and Explainable AI (XAI): A Systematic Literature Review (Research-in-Progress)

    In: Lech Janczewski; Galal H. Galal-Edeen; Barbara Krumay (Hrsg.). Proceedings of 2024 International Conference on Information Resources Management. International Conference on Information Resources Management (Conf-IRM-2024), May 26-28, Cairo, Egypt, ISBN 978-0-473-71035-4, AIS Electronic Library (AISeL), 2024.

  2. Nav-Q: Quantum Deep Reinforcement Learning for Collision-Free Navigation of Self-Driving Cars

    In: Quantum Machine Intelligence (QMI), Vol. tba, Pages 1-34, Springer, 2025.

  3. 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.

  4. 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.

  5. Gregor Duwe; Dominique Mercier; Verena Kauth; Kerstin Moench; Vikas Rajashekar; Markus Junker; Andreas Dengel; Axel Haferkamp; Thomas Hoefner

    Development of an artificial intelligence-generated, explainable treatment recommendation system for urothelial carcinoma and renal cell carcinoma to support multidisciplinary cancer conferences

    In: European Journal of Cancer (EJC), Vol. 220, No. 115367, Pages 1-8, Elsevier Ltd. 3/2025.

  6. David Antony Selby; Maximilian Sprang; Jan Ewald; Sebastian Vollmer

    Beyond the black box with biologically informed neural networks

    In: Linda Koch (Hrsg.). Nature Reviews Genetics (Nat Rev Genet), Vol. NA, Pages NA-NA, Springer Nature, 3/2025.

  7. Jonas Weigand; Gerben I. Beintema; Jonas Ulmen; Daniel Görges; Roland Tóth; Maarten Schoukens; Martin Ruskowski

    State Derivative Normalization for Continuous-Time Deep Neural Networks

    In: IFAC-PapersOnLine, Vol. 58, No. 15, Pages 253-258, ELSEVIER, 2024.

  8. Fabian Schmeisser; Maria Caroprese; Gillian Lovell; Andreas Dengel; Sheraz Ahmed

    How to Box Your Cells: An Introduction to Box Supervision for 2.5D Cell Instance Segmentation and a Study of Applications

    In: Proceedings of the 17th International Conference on Agents and Artificial Intelligence. International Conference on Agents and Artificial Intelligence (ICAART-2025), February 23-25, Porto, Portugal, Vol. 3, SciTePress, 2025.

  9. T. Vincent; F. Wahren; Jan Peters; B. Belousov; C. D'Eramo

    Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning

    In: ICML Workshop on Automated Reinforcement Learning. International Conference on Machine Learning (ICML-2024), ICML, 2024.

  10. Synthesizing Annotated Cell Microscopy Images with Generative Adversarial Networks

    In: Proceedings of the 17th International Conference on Agents and Artificial Intelligence. International Conference on Agents and Artificial Intelligence (ICAART-2025), 17th, located at ICAART-2025, February 23-25, Porto, Portugal, Pages 592-599, Vol. 3, ISBN 978-989-758-737-5, SciTePress, 2025.