3 papers
quant-ph2025
Introducing the Kernel Descent Optimizer for Variational Quantum Algorithms
Lars Simon, Holger Eble, Manuel Radons
In recent years, variational quantum algorithms have garnered significant attention as a candidate approach for near-term quantum advantage using noisy intermediate-scale quantum (…
cs.LG2025
Synthetic Data Generation and Differential Privacy using Tensor Networks' Matrix Product States (MPS)
Alejandro Moreno R., Desale Fentaw, Samuel Palmer +7
Synthetic data generation is a key technique in modern artificial intelligence, addressing data scarcity, privacy constraints, and the need for diverse datasets in training robust…
quant-ph2025
Quantum reinforcement learning in dynamic environments
Oliver Sefrin, Manuel Radons, Lars Simon +1
Combining quantum computing techniques in the form of amplitude amplification with classical reinforcement learning has led to the so-called "hybrid agent for quantum-accessible re…