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…
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…
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…
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…