Quantum generative models, in providing inherently efficient sampling
st...
Quantum process learning is emerging as an important tool to study quant...
Kernel methods in Quantum Machine Learning (QML) have recently gained
si...
Much attention has been paid to dynamical simulation and quantum machine...
Generalization bounds are a critical tool to assess the training data
re...
We consider a quantum version of the famous low-rank approximation probl...
Optimizing parameterized quantum circuits (PQCs) is the leading approach...
Moderate-size quantum computers are now publicly accessible over the clo...
Parameterized quantum circuits serve as ansätze for solving variational
...
The No-Free-Lunch (NFL) theorem is a celebrated result in learning theor...