3 papers
quant-ph2026
Parametrized-circuit-free quantum regression with variance regularization
Yerassyl Balkybek, Andrey Kardashin, Vladimir V. Palyulin +1
Quantum regression tasks for predicting properties of quantum states are commonly addressed using variational quantum algorithms. While variational quantum circuits are highly expr…
quant-ph2026
On measurement-dependent variance in quantum neural networks
Andrey Kardashin, Konstantin Antipin
Variational quantum circuits have become a widely used tool for performing quantum machine learning (QML) tasks on labeled quantum states. In some specific tasks or for specific va…
quant-ph2025
Predicting properties of quantum systems by regression on a quantum computer
Andrey Kardashin, Yerassyl Balkybek, Vladimir V. Palyulin +1
Quantum computers can be considered as a natural means for performing machine learning tasks for inherently quantum labeled data. Many quantum machine learning techniques have been…