Michiel Straat

21 papers B 4Journal 15Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Fourier neural operators as data-driven surrogates for two- and three-dimensional Rayleigh-bénard convection.
Neurocomputing
Thorben Markmann, Michiel Straat, Sebastian Peitz, Barbara Hammer
2025 J jnl
Control of Rayleigh-Bénard Convection: Effectiveness of Reinforcement Learning in the Turbulent Regime.
CoRR
Thorben Markmann, Michiel Straat, Sebastian Peitz, Barbara Hammer
2025 J jnl
Hermite polynomials facilitating on-line learning analysis of layered neural networks with arbitrary activation function.
Neurocomputing
Otavio Citton, Frederieke Richert, Michael Biehl, Michiel Straat
2025 J jnl
Improving the Robustness of Control of Chaotic Convective Flows with Domain-Informed Reinforcement Learning.
CoRR
Michiel Straat, Thorben Markmann, Sebastian Peitz, Barbara Hammer
2025 J jnl
Solving Turbulent Rayleigh-Bénard Convection using Fourier Neural Operators.
CoRR
Michiel Straat, Thorben Markmann, Barbara Hammer
2024 B conf
Koopman-Based Surrogate Modelling of Turbulent Rayleigh-Bénard Convection.
IJCNN
Thorben Markmann, Michiel Straat, Barbara Hammer
2024 J jnl
Koopman-Based Surrogate Modelling of Turbulent Rayleigh-Bénard Convection.
CoRR
Thorben Markmann, Michiel Straat, Barbara Hammer
2023 B conf
Layered Neural Networks with GELU Activation, a Statistical Mechanics Analysis.
ESANN
Frederieke Richert, Michiel Straat, Elisa Oostwal, Michael Biehl
2022 B conf
An Industry 4.0 example: real-time quality control for steel-based mass production using Machine Learning on non-invasive sensor data.
IJCNN
Michiel Straat, Kevin Koster, Nick Goet, Kerstin Bunte
2022 J jnl
An Industry 4.0 example: real-time quality control for steel-based mass production using Machine Learning on non-invasive sensor data.
CoRR
Michiel Straat, Kevin Koster, Nick Goet, Kerstin Bunte
2022 J jnl
Supervised learning in the presence of concept drift: a modelling framework.
Neural Comput. Appl.
Michiel Straat, Fthi Abadi, Zhuoyun Kan, Christina Göpfert, Barbara Hammer, Michael Biehl
2020 — conf
Complex-Valued Embeddings of Generic Proximity Data.
S+SSPR
Maximilian Münch, Michiel Straat, Michael Biehl, Frank-Michael Schleif
2020 J jnl
Complex-valued embeddings of generic proximity data.
CoRR
Maximilian Münch, Michiel Straat, Michael Biehl, Frank-Michael Schleif
2020 J jnl
Learning vector quantization and relevances in complex coefficient space.
Neural Comput. Appl.
Michiel Straat, Marika Kaden, Matthias Gay, Thomas Villmann, Alexander Lampe, Udo Seiffert, Michael Biehl, Friedrich Melchert
2020 J jnl
Supervised Learning in the Presence of Concept Drift: A modelling framework.
CoRR
Michiel Straat, Fthi Abadi, Zhuoyun Kan, Christina Göpfert, Barbara Hammer, Michael Biehl
2019 J jnl
Hidden Unit Specialization in Layered Neural Networks: ReLU vs. Sigmoidal Activation.
CoRR
Elisa Oostwal, Michiel Straat, Michael Biehl
2019 B conf
On-line learning dynamics of ReLU neural networks using statistical physics techniques.
ESANN
Michiel Straat, Michael Biehl
2019 J jnl
On-line learning dynamics of ReLU neural networks using statistical physics techniques.
CoRR
Michiel Straat, Michael Biehl
2019 J jnl
Segmentation of blood vessels in retinal fundus images.
CoRR
Michiel Straat, Jorrit Oosterhof
2018 J jnl
Statistical Mechanics of On-Line Learning Under Concept Drift.
Entropy
Michiel Straat, Fthi Abadi, Christina Göpfert, Barbara Hammer, Michael Biehl
2017 — conf
Prototypes and matrix relevance learning in complex fourier space.
WSOM
Michiel Straat, Marika Kaden, Matthias Gay, Thomas Villmann, Alexander Lampe, Udo Seiffert, Michael Biehl, Friedrich Melchert