Quantum computing and quantum neural networks: their foundation, optimisation, and application

Quantum computing and quantum neural networks: their foundation, optimisation, and application

<p>Quantum computing is a fascinating discipline, combining the laws of quantum physics with the practicalities of computing. Certain problems could potentially be solved faster on quantum computers, and researchers hope to use them to solve difficult problems in industries such as healthcare...

Descrición completa

Detalles Bibliográficos
Autor Principal:	Pointing, J
Formato:	Thesis
Idioma:	English
Publicado:	2024
Subjects:	Quantum machine learning Quantum computing Computer science Deep learning (machine learning) Artificial intelligence Neural networks (computer science) Physics

Títulos similares

Reflection equivariant quantum neural networks for enhanced image classification
por: Maxwell T West, et al.
Publicado: (2023-01-01)

Accurate Image Multi-Class Classification Neural Network Model with Quantum Entanglement Approach
por: Farina Riaz, et al.
Publicado: (2023-03-01)

Quantum cloud computing: Trends and challenges
por: Muhammed Golec, et al.
Publicado: (2024-11-01)

Reconstructing quantum states with quantum reservoir networks
por: Ghosh, Sanjib, et al.
Publicado: (2021)

Quantum Error Mitigation With Artificial Neural Network
por: Changjun Kim, et al.
Publicado: (2020-01-01)

An Overview of Quantum Machine Learning Research in China
por: Luning Li, et al.
Publicado: (2025-02-01)

Optimizing quantum convolutional neural network architectures for arbitrary data dimension
por: Changwon Lee, et al.
Publicado: (2025-03-01)

General implementation of quantum physics-informed neural networks
por: Shashank Reddy Vadyala, et al.
Publicado: (2023-07-01)

A Comparison between Invariant and Equivariant Classical and Quantum Graph Neural Networks
por: Roy T. Forestano, et al.
Publicado: (2024-02-01)

Key questions for the quantum machine learner to ask themselves
por: Nathan Wiebe
Publicado: (2020-01-01)

User trajectory prediction in mobile wireless networks using quantum reservoir computing
por: Zoubeir Mlika, et al.
Publicado: (2023-09-01)

Quantum geometric machine learning for quantum circuits and control
por: Elija Perrier, et al.
Publicado: (2020-01-01)

ℤ<sub>2</sub> × ℤ<sub>2</sub> Equivariant Quantum Neural Networks: Benchmarking against Classical Neural Networks
por: Zhongtian Dong, et al.
Publicado: (2024-03-01)

Quantum deep transfer learning
por: Longhan Wang, et al.
Publicado: (2021-01-01)

Retrieving past quantum features with deep hybrid classical-quantum reservoir computing
por: Johannes Nokkala, et al.
Publicado: (2024-01-01)

Quantum Physics-Informed Neural Networks
por: Corey Trahan, et al.
Publicado: (2024-07-01)

Trends in quantum reinforcement learning: State-of-the-arts and the road ahead
por: Soohyun Park, et al.
Publicado: (2024-10-01)

Quantum Computing for Healthcare: A Review
por: Raihan Ur Rasool, et al.
Publicado: (2023-02-01)

Guided quantum compression for high dimensional data classification
por: Vasilis Belis, et al.
Publicado: (2024-01-01)

On a quantum inspired approach to train machine learning models
por: Jean Michel Sellier
Publicado: (2023-12-01)

Quantum-Assisted Cluster Analysis on a Quantum Annealing Device
por: Florian Neukart, et al.
Publicado: (2018-06-01)

Dynamic Quantum Federated Learning for Satellite-Ground Integrated Systems Using Slimmable Quantum Neural Networks
por: Soohyun Park, et al.
Publicado: (2024-01-01)

Hybrid Quantum–Classical Neural Networks for Efficient MNIST Binary Image Classification
por: Deepak Ranga, et al.
Publicado: (2024-11-01)

Hybrid Quantum Technologies for Quantum Support Vector Machines
por: Filippo Orazi, et al.
Publicado: (2024-01-01)

Regressions on quantum neural networks at maximal expressivity
por: Iván Panadero, et al.
Publicado: (2024-12-01)

Quantum Vision Transformers for Quark–Gluon Classification
por: Marçal Comajoan Cara, et al.
Publicado: (2024-05-01)

Algorithmic models in quantum mechanics
por: Rocchetto, A
Publicado: (2019)

Hardening quantum machine learning against adversaries
por: Nathan Wiebe, et al.
Publicado: (2018-01-01)

Do quantum models make good generative learners?
por: Gili, K
Publicado: (2023)

Machine learning and quantum computing for 5G/6G communication networks - A survey
por: Suriya M
Publicado: (2022-01-01)

A Grover-search based quantum learning scheme for classification
por: Yuxuan Du, et al.
Publicado: (2021-01-01)

Quantum Computing Applications in Future Colliders
por: Heather M. Gray, et al.
Publicado: (2022-05-01)

Hybrid Quantum Neural Network Approaches to Protein–Ligand Binding Affinity Prediction
por: Maria Avramouli, et al.
Publicado: (2024-07-01)

Quantum Computing in Medicine
por: James C. L. Chow
Publicado: (2024-11-01)

Comparing Classical and Quantum Generative Learning Models for High-Fidelity Image Synthesis
por: Siddhant Jain, et al.
Publicado: (2023-12-01)

Bayesian Quantum Neural Networks
por: Nam Nguyen, et al.
Publicado: (2022-01-01)

Quantum model learning agent: characterisation of quantum systems through machine learning
por: Brian Flynn, et al.
Publicado: (2022-01-01)

Universal adversarial perturbations for multiple classification tasks with quantum classifiers
por: Yun-Zhong Qiu
Publicado: (2023-01-01)

Quantum Adversarial Transfer Learning
por: Longhan Wang, et al.
Publicado: (2023-07-01)

Quantum Machine Learning Applications in the Biomedical Domain: A Systematic Review
por: Danyal Maheshwari, et al.
Publicado: (2022-01-01)