1 citations · 1 across the 3 of their papers we have counts for
6 papers
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)…
Scalability Challenges in Variational Quantum Optimization under Stochastic Noise
Adelina Bärligea, Benedikt Poggel, Jeanette Miriam Lorenz
With rapid advances in quantum hardware, a central question is whether quantum devices with or without full error correction can outperform classical computers on practically relev…
AI-Driven Approaches for Glaucoma Detection -- A Comprehensive Review
Yuki Hagiwara, Octavia-Andreea Ciora, Maureen Monnet +2
The diagnosis of glaucoma plays a critical role in the management and treatment of this vision-threatening disease. Glaucoma is a group of eye diseases that cause blindness by dama…
Creating Automated Quantum-Assisted Solutions for Optimization Problems
Benedikt Poggel, Xiomara Runge, Adelina Bärligea +1
When trying to use quantum-enhanced methods for optimization problems, the sheer number of options inhibits its adoption by industrial end users. Expert knowledge is required for t…
Understanding the effects of data encoding on quantum-classical convolutional neural networks
Maureen Monnet, Nermine Chaabani, Theodora-Augustina Dragan +2
Quantum machine learning was recently applied to various applications and leads to results that are comparable or, in certain instances, superior to classical methods, in particula…
Efficient learning of Sparse Pauli Lindblad models for fully connected qubit topology
Jose Este Jaloveckas, Minh Tham Pham Nguyen, Lilly Palackal +2
The challenge to achieve practical quantum computing considering current hardware size and gate fidelity is the sensitivity to errors and noise. Recent work has shown that by learn…