Cover Image

Quantum parameter estimation with uncertainty quantification from continuous measurement data using neural network ensembles

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Anteneh, Amanuel
Format:	Preprint
Published:	2025
Subjects:	Quantum Physics Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Deep reinforcement learning for near-deterministic preparation of cubic- and quartic-phase gates in photonic quantum computing
by: Anteneh, Amanuel, et al.
Published: (2025)

On the uncertainty principle of neural networks
by: Zhang, Jun-Jie, et al.
Published: (2022)

Sample efficient graph classification using binary Gaussian boson sampling
by: Anteneh, Amanuel, et al.
Published: (2023)

Gradient-descent methods for scalable quantum detector tomography
by: Anteneh, Amanuel, et al.
Published: (2025)

Machine learning for efficient generation of universal hybrid quantum computing resources
by: Anteneh, Amanuel, et al.
Published: (2023)

Quantum advantage for learning shallow neural networks with natural data distributions
by: Lewis, Laura, et al.
Published: (2025)

Fast and reliable uncertainty quantification with neural network ensembles for industrial image classification
by: Thuy, Arthur, et al.
Published: (2024)

Quantum neural networks form Gaussian processes
by: García-Martín, Diego, et al.
Published: (2023)

Quantum enhanced ensemble GANs for anomaly detection in continuous biomanufacturing
by: Kailasanathan, Rajiv, et al.
Published: (2025)

Quantum neural networks facilitating quantum state classification
by: Sharma, Diksha, et al.
Published: (2025)

The effect of the number of parameters and the number of local feature patches on loss landscapes in distributed quantum neural networks
by: Kawase, Yoshiaki
Published: (2025)

Computing the gradients with respect to all parameters of a quantum neural network using a single circuit
by: He, Guang Ping
Published: (2023)

QGAN-based data augmentation for hybrid quantum-classical neural networks
by: He, Run-Ze, et al.
Published: (2025)

Hybrid quantum recurrent neural network for remaining useful life prediction
by: Tsurkan, Olga, et al.
Published: (2025)

Seismic inversion using hybrid quantum neural networks
by: Vashisth, Divakar, et al.
Published: (2025)

Quantum feedback control with a transformer neural network architecture
by: Vaidhyanathan, Pranav, et al.
Published: (2024)

Quantum continual learning of quantum data realizing knowledge backward transfer
by: Situ, Haozhen, et al.
Published: (2022)

What is my quantum computer good for? Quantum capability learning with physics-aware neural networks
by: Hothem, Daniel, et al.
Published: (2024)

Post-variational quantum neural networks
by: Huang, Po-Wei, et al.
Published: (2023)

Rapid training of quantum recurrent neural networks
by: Siemaszko, Michał, et al.
Published: (2022)

Effects of noise on the overparametrization of quantum neural networks
by: García-Martín, Diego, et al.
Published: (2023)

Feedback-driven recurrent quantum neural network universality
by: Gonon, Lukas, et al.
Published: (2025)

Reduction of finite sampling noise in quantum neural networks
by: Kreplin, David A., et al.
Published: (2023)

Resource-efficient equivariant quantum convolutional neural networks
by: Chinzei, Koki, et al.
Published: (2024)

Quantum reinforcement learning in continuous action space
by: Wu, Shaojun, et al.
Published: (2020)

Learnable quantum spectral filters for hybrid graph neural networks
by: Daskin, Ammar
Published: (2025)

On the explainability of quantum neural networks based on variational quantum circuits
by: Daskin, Ammar
Published: (2023)

Imaging at the quantum limit with convolutional neural networks
by: Proppe, Andrew H., et al.
Published: (2025)

Quantum consistent neural/tensor networks for photonic circuits with strongly/weakly entangled states
by: Allegra, Nicolas
Published: (2024)

On the effects of biased quantum random numbers on the initialization of artificial neural networks
by: Heese, Raoul, et al.
Published: (2021)

Spectral invariance and maximality properties of the frequency spectrum of quantum neural networks
by: Holzer, Patrick, et al.
Published: (2024)

A unifying primary framework for quantum graph neural networks from quantum graph states
by: Daskin, Ammar
Published: (2024)

Experimental robustness benchmarking of quantum neural networks on a superconducting quantum processor
by: Zhang, Hai-Feng, et al.
Published: (2025)

Comparing concepts of quantum and classical neural network models for image classification task
by: Potempa, Rafal, et al.
Published: (2021)

Model selection in hybrid quantum neural networks with applications to quantum transformer architectures
by: Wadhwa, Harsh, et al.
Published: (2026)

Trained quantum neural networks are Gaussian processes
by: Girardi, Filippo, et al.
Published: (2024)

Quantum time dynamics mediated by the Yang-Baxter equation and artificial neural networks
by: Gulania, Sahil, et al.
Published: (2024)

HyQuRP: Hybrid quantum-classical neural network with rotational and permutational equivariance
by: Park, Semin, et al.
Published: (2026)

QuFeX: Quantum feature extraction module for hybrid quantum-classical deep neural networks
by: Jain, Naman, et al.
Published: (2025)

Robust quantum dots charge autotuning using neural network uncertainty
by: Yon, Victor, et al.
Published: (2024)