4 citations · 4 across the 9 of their papers we have counts for
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A Semantic Framework for Reproducible Variational Quantum Algorithm Execution Records
Silvie Illésová, Martin Beseda
Variational quantum algorithms are hybrid quantum-classical workflows whose results depend on many interacting choices, including the ansatz, Hamiltonian, optimizer, backend, shot…
Classical Optimization Strategies for Variational Quantum Algorithms: A Systematic Study of Noise Effects and Parameter Efficiency
Tomáš Bezděk, Haomu Yuan, Vojtěch Novák +2
This study systematically benchmarks classical optimization strategies for the Quantum Approximate Optimization Algorithm when applied to Generalized Mean-Variance Problems under n…
Reliable Optimization Under Noise in Quantum Variational Algorithms
Vojtěch Novák, Silvie Illésová, Tomáš Bezděk +2
The optimization of Variational Quantum Eigensolver is severely challenged by finite-shot sampling noise, which distorts the cost landscape, creates false variational minima, and i…
From Classical to Hybrid: A Practical Framework for Quantum-Enhanced Learning
Silvie Illésová, Tomáš Bezděk, Vojtěch Novák +3
This work addresses the challenge of enabling practitioners without quantum expertise to transition from classical to hybrid quantum-classical machine learning workflows. We propos…
Statistical Benchmarking of Optimization Methods for Variational Quantum Eigensolver under Quantum Noise
Silvie Illésová, Tomáš Bezděk, Vojtěch Novák +2
This work investigates the performance of numerical optimization algorithms applied to the State-Averaged Orbital-Optimized Variational Quantum Eigensolver for the H2 molecule unde…
Leveraging Quantum Layers in Classical Neural Networks
Silvie Illésová
Hybrid quantum-classical neural networks represent a promising frontier in the search for improved machine learning models. This thesis explores the integration of quantum layers w…