13 citations · 41 across the 9 of their papers we have counts for
9 papers
An Energy-Based Conservative-Dissipative Latent Neural Evolution Operator for Magnetization Dynamics
Sebastian Schaffer, Lukas Exl
We develop an energy-based reduced-order model for micromagnetic magnetization dynamics that couples a convolutional autoencoder to a structured latent neural ordinary differential…
Physics-informed low-rank neural operators with application to parametric elliptic PDEs
Sebastian Schaffer, Lukas Exl
We present the Physics-Informed Low-Rank Neural Operator (PILNO), a neural operator framework for efficiently approximating solution operators of partial differential equations (PD…
Near-field-free super-potential FFT method for the three-dimensional free-space Poisson equation
Lukas Exl, Sebastian Schaffer
We present a spectrally accurate, efficient FFT-based method for the three-dimensional free-space Poisson equation with smooth, compactly supported sources. The method adopts a sup…
Higher order stray field computation on tensor product domains
Lukas Exl, Sebastian Schaffer
We present an extension of the tensor grid method for stray field computation on rectangular domains that incorporates higher-order basis functions. Both the magnetization and the…
Physics aware machine learning for micromagnetic energy minimization: recent algorithmic developments
Sebastian Schaffer, Thomas Schrefl, Harald Oezelt +2
In this work, we explore advanced machine learning techniques for minimizing Gibbs free energy in full 3D micromagnetic simulations. Building on Brown's bounds for magnetostatic se…
Physics-informed machine learning and stray field computation with application to micromagnetic energy minimization
Sebastian Schaffer, Thomas Schrefl, Harald Oezelt +5
We study the full 3d static micromagnetic equations via a physics-informed neural network (PINN) ansatz for the continuous magnetization configuration. PINNs are inherently mesh-fr…
Bridging Fidelities to Predict Nanoindentation Tip Radii Using Interpretable Deep Learning Models
Claus O. W. Trost, Stanislav Zak, Sebastian Schaffer +3
As the need for miniaturized structural and functional materials has increased,the need for precise materials characterizaton has also expanded. Nanoindentation is a popular method…
Machine learning methods for the prediction of micromagnetic magnetization dynamics
Sebastian Schaffer, Norbert J. Mauser, Thomas Schrefl +2
Machine learning (ML) entered the field of computational micromagnetics only recently. The main objective of these new approaches is the automatization of solutions of parameter-de…
Prediction of magnetization dynamics in a reduced dimensional feature space setting utilizing a low-rank kernel method
Lukas Exl, Norbert J. Mauser, Sebastian Schaffer +2
We establish a machine learning model for the prediction of the magnetization dynamics as function of the external field described by the Landau-Lifschitz-Gilbert equation, the par…