exponential integrators 1krylov methods 1low-rank approximation 1scientific computing 1stiff ODEs 1tensor train 1
From the 1 of 3 linked papers with an AI index.
3 papers
math.NA2026
Adaptive Krylov Methods for Low-Rank Exponential Integrators
Rico Weigel, Tom-Christian Riemer, Martin Stoll
The paper extends exponential integrators (KIOPS and RK2EXPINT) to work directly with low‑rank tensor‑train representations, using adaptive Krylov subspace methods to efficiently s…
math.NA2025
A Low-Rank tensor framework for THB-Splines
Tom-Christian Riemer, Martin Stoll
We introduce a low-rank framework for adaptive isogeometric analysis with truncated hierarchical B-splines (THB-splines) that targets the main bottleneck of local refinement: memor…
cs.LG2025
Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification
Jan Blechschmidt, Tom-Christian Riemer, Max Winkler +2
We develop a novel physics informed deep learning approach for solving nonlinear drift-diffusion equations on metric graphs. These models represent an important model class with a…