Michiel Straat

According to our database, Michiel Straat authored at least 11 papers between 2017 and 2024.

Collaborative distances:

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

2024

Koopman-Based Surrogate Modelling of Turbulent Rayleigh-Bénard Convection.

Thorben Markmann, Michiel Straat, Barbara Hammer

Proceedings of the International Joint Conference on Neural Networks, 2024

2023

Layered Neural Networks with GELU Activation, a Statistical Mechanics Analysis.

Frederieke Richert, Michiel Straat, Elisa Oostwal, Michael Biehl

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

2022

Supervised learning in the presence of concept drift: a modelling framework.

Michiel Straat, Fthi Abadi, Zhuoyun Kan, Christina Göpfert, Barbara Hammer, Michael Biehl

Neural Comput. Appl., 2022

An Industry 4.0 example: real-time quality control for steel-based mass production using Machine Learning on non-invasive sensor data.

Michiel Straat, Kevin Koster, Nick Goet, Kerstin Bunte

Proceedings of the International Joint Conference on Neural Networks, 2022

2020

Learning vector quantization and relevances in complex coefficient space.

Michiel Straat, Marika Kaden, Matthias Gay, Thomas Villmann, Alexander Lampe, Udo Seiffert, Michael Biehl, Friedrich Melchert

Neural Comput. Appl., 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

2019

Hidden Unit Specialization in Layered Neural Networks: ReLU vs. Sigmoidal Activation.

Elisa Oostwal, Michiel Straat, Michael Biehl

CoRR, 2019

Segmentation of blood vessels in retinal fundus images.

Michiel Straat, Jorrit Oosterhof

CoRR, 2019

On-line learning dynamics of ReLU neural networks using statistical physics techniques.

Michiel Straat, Michael Biehl

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

2018

Statistical Mechanics of On-Line Learning Under Concept Drift.

Michiel Straat, Fthi Abadi, Christina Göpfert, Barbara Hammer, Michael Biehl

Entropy, 2018

2017

Prototypes and matrix relevance learning in complex fourier space.

Michiel Straat, Marika Kaden, Matthias Gay, Thomas Villmann, Alexander Lampe, Udo Seiffert, Michael Biehl, Friedrich Melchert

Proceedings of the 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, 2017