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

• 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

• 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

• 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

• 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

• FairGLVQ: Fairness in Partition-Based Classification (2024)

  Authors: Felix Störck, Fabian Hinder, Johannes Brinkrolf, Benjamin Paassen, Valerie Vaquet, Barbara Hammer

  Published at: Lecture Notes in Networks and Systems (Volume: 1087 LNNS)
  DOI: 10.1007/978-3-031-67159-3_17

• One or two things we know about concept drift—a survey on monitoring in evolving environments. Part B: locating and explaining concept drift (2024)

  Authors: Fabian Hinder, Valerie Vaquet, Barbara Hammer

  Published at: Frontiers in Artificial Intelligence (Volume: 7)
  DOI: 10.3389/frai.2024.1330258

• One or two things we know about concept drift—a survey on monitoring in evolving environments. Part A: detecting concept drift (2024)

  Authors: Fabian Hinder, Valerie Vaquet, Barbara Hammer

  Published at: Frontiers in Artificial Intelligence (Volume: 7)
  DOI: 10.3389/frai.2024.1330257

• Novel approach for data-driven modelling of multi-stage straightening and bending processes (2024)

  Authors: Henning Peters, Eugen Djakow, Tim Rostek, Andreas Mazur, Ansgar Trächtler, Werner Homberg, Barbara Hammer

  Published at: Materials Research Proceedings (Volume: 41)
  DOI: 10.21741/9781644903131-252

• SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification (2024)

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

  Published at: Proceedings of Machine Learning Research (Volume: 238)