Towards a device-free passive presence detection system with Bluetooth Low Energy beacons. - Maximilian Münch; Karsten Huffstadt; Frank-Michael Schleif (ESANN, 2019)

Device-Free Passive Human Counting with Bluetooth Low Energy Beacons. - Maximilian Münch; Frank-Michael Schleif (IWANN (2), 2019)

Structure Preserving Encoding of Non-euclidean Similarity Data. - Maximilian Münch; Christoph Raab; Michael Biehl; Frank-Michael Schleif (ICPRAM, 2020)

Encoding of Indefinite Proximity Data: A Structure Preserving Perspective. - Maximilian Münch; Christoph Raab; Frank-Michael Schleif (ICPRAM (Revised Selected Papers), 2020)

Complex-Valued Embeddings of Generic Proximity Data. - Maximilian Münch; Michiel Straat; Michael Biehl; Frank-Michael Schleif (S+SSPR, 2020)

Data-Driven Supervised Learning for Life Science Data. - Maximilian Münch; Christoph Raab; Michael Biehl; Frank-Michael Schleif (Frontiers Appl. Math. Stat., 2020)

Multi-perspective embedding for non-metric time series classification. - Maximilian Münch; Simon Heilig; Frank-Michael Schleif (ESANN, 2021)

Scalable embedding of multiple perspectives for indefinite life-science data analysis. - Maximilian Münch; Simon Heilig; Philipp Väth; Frank-Michael Schleif (SSCI, 2021)

Revisiting Memory Efficient Kernel Approximation: An Indefinite Learning Perspective. - Simon Heilig; Maximilian Münch; Frank-Michael Schleif (CoRR, 2021)

Adaptive multi-modal positive semi-definite and indefinite kernel fusion for binary classification. - Maximilian Münch; Christoph Raab; Simon Heilig; Manuel Röder; Frank-Michael Schleif (ESANN, 2022)

Memory Efficient Kernel Approximation for Non-Stationary and Indefinite Kernels. - Simon Heilig; Maximilian Münch; Frank-Michael Schleif (IJCNN, 2022)

Unlocking the Potential of Non-PSD Kernel Matrices: A Polar Decomposition-based Transformation for Improved Prediction Models. - Maximilian Münch; Manuel Röder; Frank-Michael Schleif (CIKM, 2023)

Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed Landmark Selection. - Maximilian Münch; Katrin Sophie Bohnsack; Alexander Engelsberger; Frank-Michael Schleif; Thomas Villmann (ESANN, 2023)

Efficient Cross-Domain Federated Learning by MixStyle Approximation. - Manuel Röder; Leon Heller; Maximilian Münch; Frank-Michael Schleif (CoRR, 2023)

Static and adaptive subspace information fusion for indefinite heterogeneous proximity data. - Maximilian Münch; Manuel Röder; Simon Heilig; Christoph Raab; Frank-Michael Schleif (Neurocomputing, 2023)

Crossing Domain Borders with Federated Few-Shot Adaptation. - Manuel Röder; Maximilian Münch; Christoph Raab; Frank-Michael Schleif (ICPRAM, 2024)