Quantum process learning is emerging as an important tool to study quant...
At the intersection of machine learning and quantum computing, Quantum
M...
Many Artificial Intelligence (AI) algorithms are inspired by physics and...
Quantum-enhanced data science, also known as quantum machine learning (Q...
Most currently used quantum neural network architectures have little-to-...
Recent advances in classical machine learning have shown that creating m...
We study the problem of learning the parameters for the Hamiltonian of a...
In a standard Quantum Sensing (QS) task one aims at estimating an unknow...
Quantum Machine Learning (QML) models are aimed at learning from data en...
Much attention has been paid to dynamical simulation and quantum machine...
Generalization bounds are a critical tool to assess the training data
re...
Principal component analysis (PCA) is a dimensionality reduction method ...
We consider a quantum version of the famous low-rank approximation probl...
A semidefinite program (SDP) is a particular kind of convex optimization...
Modern quantum machine learning (QML) methods involve variationally
opti...
A new paradigm for data science has emerged, with quantum data, quantum
...
The prospect of achieving quantum advantage with Quantum Neural Networks...
High-quality, large-scale datasets have played a crucial role in the
dev...
Variational Quantum Algorithms (VQAs) are widely viewed as the best hope...
Variational Quantum Algorithms (VQAs) are a promising approach for pract...
Optimizing parameterized quantum circuits (PQCs) is the leading approach...
Quantum machine learning (QML) offers a powerful, flexible paradigm for
...
Moderate-size quantum computers are now publicly accessible over the clo...
Parameterized quantum circuits serve as ansätze for solving variational
...
Applications such as simulating large quantum systems or solving large-s...
Barren plateau landscapes correspond to gradients that vanish exponentia...
Very little is known about the cost landscape for parametrized Quantum
C...
Quantum neural networks (QNNs) have generated excitement around the
poss...
Variational Quantum Algorithms (VQAs) may be a path to quantum advantage...
The No-Free-Lunch (NFL) theorem is a celebrated result in learning theor...
Several architectures have been proposed for quantum neural networks (QN...
Variational quantum algorithms (VQAs) optimize the parameters
θ of a qua...