Time integration methods in micromagnetic simulations: stiffness on granular media and MMAG standard problem #4-Speed up of simulations in granular recording media. - Vassilios D. Tsiantos; Thomas Schrefl; Dieter Suess; Werner Scholz; Hermann Forster; Josef Fidler (HERCMA, 2001)

Performance of a Novel Algorithm for Perpendicular Magnetic Recording Simulation. - Dennis M. Newns; Wilm E. Donath; Glenn J. Martyna; Manfred E. Schabes; Byron H. Lengsfield III; Thomas Schrefl (IPDPS, 2002)

Kronecker product approximation of demagnetizing tensors for micromagnetics. - A. V. Goncharov; Gino Hrkac; J. S. Dean; Thomas Schrefl (J. Comput. Phys., 2010)

Self-organizing magnetic beads for biomedical applications - Markus Gusenbauer; Alexander Kovacs; Franz Reichel; Lukas Exl; Simon Bance; Harald Oezelt; Thomas Schrefl (CoRR, 2011)

A tunable cancer cell filter using magnetic beads: cellular and fluid dynamic simulations - Markus Gusenbauer; Ivan Cimrák; Simon Bance; Lukas Exl; Franz Reichel; Harald Oezelt; Thomas Schrefl (CoRR, 2011)

Modelling and simulation of processes in microfluidic devices for biomedical applications. - Ivan Cimrák; Markus Gusenbauer; Thomas Schrefl (Comput. Math. Appl., 2012)

Fast stray field computation on tensor grids. - Lukas Exl; Winfried Auzinger; Simon Bance; Markus Gusenbauer; Franz Reichel; Thomas Schrefl (J. Comput. Phys., 2012)

Simulation of magnetic active polymers for versatile microfluidic devices - Markus Gusenbauer; Harald Özelt; Johann Fischbacher; Franz Reichel; Lukas Exl; Simon Bance; Nadezhda Kataeva; Claudia Binder; Hubert Brückl; Thomas Schrefl (CoRR, 2013)

Guided self-assembly of magnetic beads for biomedical applications - Markus Gusenbauer; Ha Nguyen; Franz Reichel; Lukas Exl; Simon Bance; Johann Fischbacher; Harald Özelt; Alexander Kovacs; Martin Brandl; Thomas Schrefl (CoRR, 2013)

Non-uniform FFT for the finite element computation of the micromagnetic scalar potential. - Lukas Exl; Thomas Schrefl (J. Comput. Phys., 2014)

Sensing the blood cell damage in a magnetically actuated circular pump. - Markus Gusenbauer; Giulia Mazza; Martin Brandl; Thomas Schrefl (IEEE SENSORS, 2017)

The extrapolated explicit midpoint scheme for variable order and step size controlled integration of the Landau-Lifschitz-Gilbert equation. - Lukas Exl; Norbert J. Mauser; Thomas Schrefl; Dieter Suess (J. Comput. Phys., 2017)

Extracting local switching fields in permanent magnets using machine learning. - Markus Gusenbauer; Harald Oezelt; Johann Fischbacher; Alexander Kovacs; Panpan Zhao; Thomas George Woodcock; Thomas Schrefl (CoRR, 2019)

Preconditioned nonlinear conjugate gradient method for micromagnetic energy minimization. - Lukas Exl; Johann Fischbacher; Alexander Kovacs; Harald Oezelt; Markus Gusenbauer; Thomas Schrefl (Comput. Phys. Commun., 2019)

Learning time-stepping by nonlinear dimensionality reduction to predict magnetization dynamics. - Lukas Exl; Norbert J. Mauser; Thomas Schrefl; Dieter Suess (Commun. Nonlinear Sci. Numer. Simul., 2020)

Prediction of magnetization dynamics in a reduced dimensional feature space setting utilizing a low-rank kernel method. - Lukas Exl; Norbert J. Mauser; Sebastian Schaffer; Thomas Schrefl; Dieter Suess (J. Comput. Phys., 2021)

Conditional physics informed neural networks. - Alexander Kovacs; Lukas Exl; Alexander Kornell; Johann Fischbacher; Markus Hovorka; Markus Gusenbauer; Leoni Breth; Harald Oezelt; Masao Yano; Noritsugu Sakuma; Akihito Kinoshita; Tetsuya Shoji; et al. (Commun. Nonlinear Sci. Numer. Simul., 2022)

Physics aware machine learning for micromagnetic energy minimization: Recent algorithmic developments. - Sebastian Schaffer; Thomas Schrefl; Harald Oezelt; Norbert J. Mauser; Lukas Exl (Comput. Phys. Commun., 2025)