A review of barren plateaus in variational quantum computing
Variational quantum computing offers a flexible computational paradigm with applications in
diverse areas. However, a key obstacle to realizing their potential is the Barren Plateau (BP) …
diverse areas. However, a key obstacle to realizing their potential is the Barren Plateau (BP) …
Enforcing exact permutation and rotational symmetries in the application of quantum neural networks on point cloud datasets
Z Li, L Nagano, K Terashi - Physical Review Research, 2024 - APS
Recent developments in the field of quantum machine learning have promoted the idea of
incorporating physical symmetries in the structure of quantum circuits. A crucial milestone in …
incorporating physical symmetries in the structure of quantum circuits. A crucial milestone in …
Dynamical transition in controllable quantum neural networks with large depth
Understanding the training dynamics of quantum neural networks is a fundamental task in
quantum information science with wide impact in physics, chemistry and machine learning …
quantum information science with wide impact in physics, chemistry and machine learning …
Quantum machine learning for Lyapunov-stabilized computation offloading in next-generation MEC networks
VR Verma, DK Nishad, V Sharma, VK Singh… - Scientific Reports, 2025 - nature.com
Quantum computing and machine learning convergence enable powerful new approaches
for optimizing mobile edge computing (MEC) networks. This paper uses Lyapunov …
for optimizing mobile edge computing (MEC) networks. This paper uses Lyapunov …
Quantitative convergence of trained quantum neural networks to a Gaussian process
AM Hernandez, F Girardi, D Pastorello… - arXiv preprint arXiv …, 2024 - arxiv.org
We study quantum neural networks where the generated function is the expectation value of
the sum of single-qubit observables across all qubits. In [Girardi\emph {et al.}, arXiv …
the sum of single-qubit observables across all qubits. In [Girardi\emph {et al.}, arXiv …
Quantum-data-driven dynamical transition in quantum learning
Quantum circuits are an essential ingredient of quantum information processing.
Parameterized quantum circuits optimized under a specific cost function--quantum neural …
Parameterized quantum circuits optimized under a specific cost function--quantum neural …