8 citations · 9 across the 9 of their papers we have counts for
4 papers · 1 filter
The QuaST Decision Tree: Achieving Automation With Data-Based Recommendations
Benedikt Poggel, Lena Tokuhiro, Georg Kruse +1
Quantum computers are increasingly powerful. Software tools for the development of quantum-enhanced algorithms are maturing. However, the software stack still lacks the connection…
jNO: A JAX Library for Neural Operator and Foundation Model Training
Leon Armbruster, Rathan Ramesh, Georg Kruse +1
jNO (jax Neural Operators) is a JAX-native library for neural operators and foundation models with unified support for both data-driven and physics-informed training. Its core desi…
Physics-informed fine-tuning of foundation models for partial differential equations
Vlad Medvedev, Leon Armbruster, Christopher Straub +2
Foundation models for partial differential equations (PDEs) have emerged as powerful surrogates pre-trained on diverse physical systems, but adapting them to new downstream tasks r…
QAOA-Predictor: Forecasting Success Probabilities and Minimal Depths for Efficient Fixed-Parameter Optimization
Rodrigo Coelho, Georg Kruse, Jeanette Miriam Lorenz
Quantum Computing promises to solve complex combinatorial optimization problems more efficiently than classical methods, with the Quantum Approximate Optimization Algorithm (QAOA)…