4 papers
Algorithmic algorithm development with LLMs: A Case Study on LLM-Usage for Contraction Order Optimization in Tensor Networks
Fabian Hoppe, Melven Röhrig-Zöllner, Philipp Knechtges
We consider LLM-based algorithm development through a case study on contractionorder optimisation for tensor networks with OpenEvolve. We pay particular attention to the choice of…
Preconditioned FEM-based Neural Networks for Solving Incompressible Fluid Flows and Related Inverse Problems
Franziska Griese, Fabian Hoppe, Alexander Rüttgers +1
The numerical simulation and optimization of technical systems described by partial differential equations is expensive, especially in multi-query scenarios in which the underlying…
Sparse Bayesian Learning for Label Efficiency in Cardiac Real-Time MRI
Felix Terhag, Philipp Knechtges, Achim Basermann +4
Cardiac real-time magnetic resonance imaging (MRI) is an emerging technology that images the heart at up to 50 frames per second, offering insight into the respiratory effects on t…
Uncertainty Quantification in Machine Learning Based Segmentation: A Post-Hoc Approach for Left Ventricle Volume Estimation in MRI
F. Terhag, P. Knechtges, A. Basermann +1
Recent studies have confirmed cardiovascular diseases remain responsible for highest death toll amongst non-communicable diseases. Accurate left ventricular (LV) volume estimation…