Michiel Straat

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 15

Top Topics

Statistical Mechanics

Deterministic Annealing

Top Venues

Neural Comput. Appl.

Publications

Thorben Markmann, Michiel Straat, Barbara Hammer
Koopman-Based Surrogate Modelling of Turbulent Rayleigh-Bénard Convection. CoRR (2024)
Frederieke Richert, Michiel Straat, Elisa Oostwal, Michael Biehl
Layered Neural Networks with GELU Activation, a Statistical Mechanics Analysis. ESANN (2023)
Michiel Straat, Fthi Abadi, Zhuoyun Kan, Christina Göpfert, Barbara Hammer, Michael Biehl
Supervised learning in the presence of concept drift: a modelling framework. Neural Comput. Appl. 34 (1) (2022)
Michiel Straat, Kevin Koster, Nick Goet, Kerstin Bunte
An Industry 4.0 example: real-time quality control for steel-based mass production using Machine Learning on non-invasive sensor data. CoRR (2022)
Michiel Straat, Kevin Koster, Nick Goet, Kerstin Bunte
An Industry 4.0 example: real-time quality control for steel-based mass production using Machine Learning on non-invasive sensor data. IJCNN (2022)
Michiel Straat, Marika Kaden, Matthias Gay, Thomas Villmann, Alexander Lampe, Udo Seiffert, Michael Biehl, Friedrich Melchert
Learning vector quantization and relevances in complex coefficient space. Neural Comput. Appl. 32 (24) (2020)
Michiel Straat, Fthi Abadi, Zhuoyun Kan, Christina Göpfert, Barbara Hammer, Michael Biehl
Supervised Learning in the Presence of Concept Drift: A modelling framework. CoRR (2020)
Maximilian Münch, Michiel Straat, Michael Biehl, Frank-Michael Schleif
Complex-valued embeddings of generic proximity data. CoRR (2020)
Maximilian Münch, Michiel Straat, Michael Biehl, Frank-Michael Schleif
Complex-Valued Embeddings of Generic Proximity Data. S+SSPR (2020)
Michiel Straat, Jorrit Oosterhof
Segmentation of blood vessels in retinal fundus images. CoRR (2019)
Elisa Oostwal, Michiel Straat, Michael Biehl
Hidden Unit Specialization in Layered Neural Networks: ReLU vs. Sigmoidal Activation. CoRR (2019)
Michiel Straat, Michael Biehl
On-line learning dynamics of ReLU neural networks using statistical physics techniques. ESANN (2019)
Michiel Straat, Michael Biehl
On-line learning dynamics of ReLU neural networks using statistical physics techniques. CoRR (2019)
Michiel Straat, Fthi Abadi, Christina Göpfert, Barbara Hammer, Michael Biehl
Statistical Mechanics of On-Line Learning Under Concept Drift. Entropy 20 (10) (2018)
Michiel Straat, Marika Kaden, Matthias Gay, Thomas Villmann, Alexander Lampe, Udo Seiffert, Michael Biehl, Friedrich Melchert
Prototypes and matrix relevance learning in complex fourier space. WSOM (2017)