3 citations · 4 across the 7 of their papers we have counts for
3 papers · 1 filter
Assessing Cost Hamiltonian Reliability in Quantum Protein Structure Prediction
Mathieu Roget, Cedric Damour, Frederic Cadet +1
In variational quantum algorithms, QAOA, and quantum annealing, the cost Hamiltonian defines the optimization landscape explored by the quantum hardware; however, in many applicati…
Quantum Autoencoder: An efficient approach to quantum feature map generation
Shengxin Zhuang, Yusen Wu, Xavier F. Cadet +6
Quantum machine learning methods often rely on fixed, hand-crafted quantum encodings that may not capture optimal features for downstream tasks. In this work, we study the power of…
Non-Hemolytic Peptide Classification Using A Quantum Support Vector Machine
Shengxin Zhuang, John Tanner, Yusen Wu +7
Quantum machine learning (QML) is one of the most promising applications of quantum computation. However, it is still unclear whether quantum advantages exist when the data is of a…