Maximilian Münch

According to our database, Maximilian Münch authored at least 16 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Crossing Domain Borders with Federated Few-Shot Adaptation.

Manuel Röder, Maximilian Münch, Christoph Raab, Frank-Michael Schleif

Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods, 2024

2023

Static and adaptive subspace information fusion for indefinite heterogeneous proximity data.

Maximilian Münch, Manuel Röder, Simon Heilig, Christoph Raab, Frank-Michael Schleif

Neurocomputing, October, 2023

Efficient Cross-Domain Federated Learning by MixStyle Approximation.

Manuel Röder, Leon Heller, Maximilian Münch, Frank-Michael Schleif

CoRR, 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

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Unlocking the Potential of Non-PSD Kernel Matrices: A Polar Decomposition-based Transformation for Improved Prediction Models.

Maximilian Münch, Manuel Röder, Frank-Michael Schleif

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Memory Efficient Kernel Approximation for Non-Stationary and Indefinite Kernels.

Simon Heilig, Maximilian Münch, Frank-Michael Schleif

Proceedings of the International Joint Conference on Neural Networks, 2022

Adaptive multi-modal positive semi-definite and indefinite kernel fusion for binary classification.

Maximilian Münch, Christoph Raab, Simon Heilig, Manuel Röder, Frank-Michael Schleif

Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021

Revisiting Memory Efficient Kernel Approximation: An Indefinite Learning Perspective.

Simon Heilig, Maximilian Münch, Frank-Michael Schleif

CoRR, 2021

Scalable embedding of multiple perspectives for indefinite life-science data analysis.

Maximilian Münch, Simon Heilig, Philipp Väth, Frank-Michael Schleif

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Multi-perspective embedding for non-metric time series classification.

Maximilian Münch, Simon Heilig, Frank-Michael Schleif

Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

2020

Data-Driven Supervised Learning for Life Science Data.

Maximilian Münch, Christoph Raab, Michael Biehl, Frank-Michael Schleif

Frontiers Appl. Math. Stat., 2020

Complex-Valued Embeddings of Generic Proximity Data.

Maximilian Münch, Michiel Straat, Michael Biehl, Frank-Michael Schleif

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2020

Encoding of Indefinite Proximity Data: A Structure Preserving Perspective.

Maximilian Münch, Christoph Raab, Frank-Michael Schleif

Proceedings of the Pattern Recognition Applications and Methods, 2020

Structure Preserving Encoding of Non-euclidean Similarity Data.

Maximilian Münch, Christoph Raab, Michael Biehl, Frank-Michael Schleif

Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods, 2020

2019

Device-Free Passive Human Counting with Bluetooth Low Energy Beacons.

Maximilian Münch, Frank-Michael Schleif

Proceedings of the Advances in Computational Intelligence, 2019

Towards a device-free passive presence detection system with Bluetooth Low Energy beacons.

Maximilian Münch, Karsten Huffstadt, Frank-Michael Schleif

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019