Probabilistic extension and reject options for pairwise LVQ. - Johannes Brinkrolf; Barbara Hammer (WSOM, 2017)

Efficient kernelisation of discriminative dimensionality reduction. - Alexander Schulz 001; Johannes Brinkrolf; Barbara Hammer (Neurocomputing, 2017)

Differential private relevance learning. - Johannes Brinkrolf; Kolja Berger; Barbara Hammer (ESANN, 2018)

Interpretable machine learning with reject option. - Johannes Brinkrolf; Barbara Hammer (Autom., 2018)

Differential privacy for learning vector quantization. - Johannes Brinkrolf; Christina Göpfert; Barbara Hammer (Neurocomputing, 2019)

Sparse Metric Learning in Prototype-based Classification. - Johannes Brinkrolf; Barbara Hammer (ESANN, 2020)

Time integration and reject options for probabilistic output of pairwise LVQ. - Johannes Brinkrolf; Barbara Hammer (Neural Comput. Appl., 2020)

Federated Learning Vector Quantization. - Johannes Brinkrolf; Barbara Hammer (ESANN, 2021)

Evaluating Robustness of Counterfactual Explanations. - André Artelt; Valerie Vaquet; Riza Velioglu; Fabian Hinder; Johannes Brinkrolf; Malte Schilling; Barbara Hammer (SSCI, 2021)

A Shape-Based Method for Concept Drift Detection and Signal Denoising. - Fabian Hinder; Johannes Brinkrolf; Valerie Vaquet; Barbara Hammer (SSCI, 2021)

Fast Non-Parametric Conditional Density Estimation using Moment Trees. - Fabian Hinder; Valerie Vaquet; Johannes Brinkrolf; Barbara Hammer (SSCI, 2021)

Online Learning on Non-Stationary Data Streams for Image Recognition using Deep Embeddings. - Valerie Vaquet; Fabian Hinder; Jonas Vaquet; Johannes Brinkrolf; Barbara Hammer (SSCI, 2021)

Federated learning vector quantization for dealing with drift between nodes. - Johannes Brinkrolf; Valerie Vaquet; Fabian Hinder; Patrick Menz; Udo Seiffert; Barbara Hammer (ESANN, 2022)

Feature Selection for Trustworthy Regression Using Higher Moments. - Fabian Hinder; Johannes Brinkrolf; Barbara Hammer (ICANN (4), 2022)

Taking Care of Our Drinking Water: Dealing with Sensor Faults in Water Distribution Networks. - Valerie Vaquet; André Artelt; Johannes Brinkrolf; Barbara Hammer (ICANN (2), 2022)

Explaining Reject Options of Learning Vector Quantization Classifiers. - André Artelt; Johannes Brinkrolf; Roel Visser; Barbara Hammer (IJCCI, 2022)

Localization of Concept Drift: Identifying the Drifting Datapoints. - Fabian Hinder; Valerie Vaquet; Johannes Brinkrolf; André Artelt; Barbara Hammer (IJCNN, 2022)

On the Change of Decision Boundaries and Loss in Learning with Concept Drift. - Fabian Hinder; Valerie Vaquet; Johannes Brinkrolf; Barbara Hammer (CoRR, 2022)

Robust Feature Selection and Robust Training to Cope with Hyperspectral Sensor Shifts. - Valerie Vaquet; Johannes Brinkrolf; Barbara Hammer (ESANN, 2023)

On the Hardness and Necessity of Supervised Concept Drift Detection. - Fabian Hinder; Valerie Vaquet; Johannes Brinkrolf; Barbara Hammer (ICPRAM, 2023)

On the Change of Decision Boundary and Loss in Learning with Concept Drift. - Fabian Hinder; Valerie Vaquet; Johannes Brinkrolf; Barbara Hammer (IDA, 2023)

Combining self-labeling and demand based active learning for non-stationary data streams. - Valerie Vaquet; Fabian Hinder; Johannes Brinkrolf; Barbara Hammer (CoRR, 2023)

Learning Vector Quantization for the Real-World: Privacy, Robustness, and Sparsity. - Johannes Brinkrolf (2023)

Model-based explanations of concept drift. - Fabian Hinder; Valerie Vaquet; Johannes Brinkrolf; Barbara Hammer (Neurocomputing, 2023)

Causes of Rejects in Prototype-based Classification Aleatoric vs. Epistemic Uncertainty. - Johannes Brinkrolf; Valerie Vaquet; Fabian Hinder; Barbara Hammer (ESANN, 2024)

Challenges, Methods, Data-A Survey of Machine Learning in Water Distribution Networks. - Valerie Vaquet; Fabian Hinder; André Artelt; Inaam Ashraf; Janine Strotherm; Jonas Vaquet; Johannes Brinkrolf; Barbara Hammer (ICANN (9), 2024)

FairGLVQ: Fairness in Partition-Based Classification. - Felix Störck; Fabian Hinder; Johannes Brinkrolf; Benjamin Paassen; Valerie Vaquet; Barbara Hammer (WSOM+, 2024)