Barbara Hammer

Sustainable AI, Hybrid Systems, Computational Learning Theory, Applications for Critical Infrastructure

Incremental learning and learning with drift, learning from limited data set, learning with label noise or few labels, reliability of learning, efficient deep learning, fairness of ML; explainable ML, readability of learning, learning with structured data, prototype-based models, graph neural networks, recurrent and recursive models; biomedical applications

• Trust, distrust, and appropriate reliance in (X)AI: A conceptual clarification of user trust and survey of its empirical evaluation (2025)

  Authors: Roel Visser, Tobias M. Peters, Ingrid Scharlau, Barbara Hammer

  Published at: Cognitive Systems Research (Volume: 91)
  DOI: 10.1016/j.cogsys.2025.101357

• A Benchmark for Physics-informed Machine Learning of Chlorine Concentration States in Water Distribution Networks (2025)

  Authors: Luca Hermes, André Artelt, Stelios G. Vrachimis, Marios M. Polycarpou, Barbara Hammer

  Published at: SN Computer Science (Volume: 6)
  DOI: 10.1007/s42979-025-04008-y

• Development of a digital twin for data-driven modeling of punch-bending processes using a graphical modeling notation (2025)

  Authors: Henning Peters, Andreas Mazur, Ankit Kumar Pandey, Ansgar Trächtler, Barbara Hammer, Werner Homberg

  Published at: At Automatisierungstechnik (Volume: 73)
  DOI: 10.1515/auto-2024-0112

• Towards Reliable Drift Detection and Explanation in Text Data (2025)

  Authors: Robert Feldhans, Barbara Hammer

  Published at: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics (Volume: 15346 LNCS)
  DOI: 10.1007/978-3-031-77731-8_28

• Generating Cardiovascular Data by Integration of Physiological Information (2025)

  Authors: Johannes Kummert, Alexander Schulz, Moriz Habigt, Maike Stemmler, Christina Kohler, Dirk Abel, Rolf Rossaint, Barbara Hammer

  Published at: 2025 IEEE Symposium on Computational Intelligence in Health and Medicine Cihm 2025
  DOI: 10.1109/CIHM64979.2025.10969490

• Feature-based analyses of concept drift (2024)

  Authors: Fabian Hinder, Valerie Vaquet, Barbara Hammer

  Published at: Neurocomputing (Volume: 600)
  DOI: 10.1016/j.neucom.2024.127968

• Modularity in Nervous Systems—a Key to Efficient Adaptivity for Deep Reinforcement Learning (2024)

  Authors: Malte Schilling, Barbara Hammer, Frank W. Ohl, Helge J. Ritter, Laurenz Wiskott

  Published at: Cognitive Computation (Volume: 16)
  DOI: 10.1007/s12559-022-10080-w

• Physics-Informed Graph Neural Networks forWater Distribution Systems (2024)

  Authors: Inaam Ashraf, Janine Strotherm, Luca Hermes, Barbara Hammer

  Published at: Proceedings of the Aaai Conference on Artificial Intelligence (Volume: 38)
  DOI: 10.1609/aaai.v38i20.30192

• Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles (2024)

  Authors: Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier

  Published at: Proceedings of the Aaai Conference on Artificial Intelligence (Volume: 38)
  DOI: 10.1609/aaai.v38i13.29352

• Explaining Neural Networks - Deep and Shallow (2024)

  Authors: Barbara Hammer

  Published at: Lecture Notes in Networks and Systems (Volume: 1087 LNNS)
  DOI: 10.1007/978-3-031-67159-3_16