Imagen de Portada

A comprehensive review of Quantum Machine Learning: from NISQ to Fault Tolerance

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Wang, Yunfei, Liu, Junyu
Formato:	Preprint
Publicado:	2024
Materias:	Quantum Physics Artificial Intelligence Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Scalable Neural Decoders for Practical Fault-Tolerant Quantum Computation
por: Gu, Andi, et al.
Publicado: (2026)

The Stabilizer Bootstrap of Quantum Machine Learning with up to 10000 qubits
por: Li, Yuqing, et al.
Publicado: (2024)

Laziness, Barren Plateau, and Noise in Machine Learning
por: Liu, Junyu, et al.
Publicado: (2022)

Fundamental causal bounds of quantum random access memories
por: Wang, Yunfei, et al.
Publicado: (2023)

The Efficiency Frontier: Classical Shadows versus Quantum Footage
por: Ma, Shuowei, et al.
Publicado: (2025)

Quantum Error Mitigation with Attention Graph Transformers for Burgers Equation Solvers on NISQ Hardware
por: Tousi, Seyed Mohamad Ali, et al.
Publicado: (2025)

Implementing Pearl's $\mathcal{DO}$-Calculus on Quantum Circuits: A Simpson-Type Case Study on NISQ Hardware
por: Kang, Pilsung
Publicado: (2025)

Enhancing Quantum Security over Federated Learning via Post-Quantum Cryptography
por: Li, Pingzhi, et al.
Publicado: (2024)

Q-Newton: Hybrid Quantum-Classical Scheduling for Accelerating Neural Network Training with Newton's Gradient Descent
por: Li, Pingzhi, et al.
Publicado: (2024)

Quantum Machine Learning: A Hands-on Tutorial for Machine Learning Practitioners and Researchers
por: Du, Yuxuan, et al.
Publicado: (2025)

An Analytic Theory of Quantum Imaginary Time Evolution
por: Chen, Min, et al.
Publicado: (2025)

Quantum Data Center: Perspectives
por: Liu, Junyu, et al.
Publicado: (2023)

A Primer on Quantum Machine Learning
por: Chang, Su Yeon, et al.
Publicado: (2025)

GroverGPT: A Large Language Model with 8 Billion Parameters for Quantum Searching
por: Wang, Haoran, et al.
Publicado: (2024)

Scalable Community Detection Using Quantum Hamiltonian Descent and QUBO Formulation
por: Cheng, Jinglei, et al.
Publicado: (2024)

Symbolic Analysis of Grover Search Algorithm via Chain-of-Thought Reasoning and Quantum-Native Tokenization
por: Chen, Min, et al.
Publicado: (2025)

Quantum Circuit-Based Learning Models: Bridging Quantum Computing and Machine Learning
por: Fan, Fan, et al.
Publicado: (2026)

Quantum Architecture Search for Solving Quantum Machine Learning Tasks
por: Kölle, Michael, et al.
Publicado: (2025)

Identification and Mitigating Bias in Quantum Machine Learning
por: Swaminathan, Nandhini, et al.
Publicado: (2024)

Toward Super-polynomial Quantum Speedup of Equivariant Quantum Algorithms with SU($d$) Symmetry
por: Zheng, Han, et al.
Publicado: (2022)

Embedding-Aware Quantum-Classical SVMs for Scalable Quantum Machine Learning
por: Ordóñez, Sebastián Andrés Cajas, et al.
Publicado: (2025)

Machine Learning and Quantum Intelligence for Health Data Scenarios
por: Naguleswaran, Sanjeev
Publicado: (2024)

Quantum Machine Learning for Anomaly Detection in Consumer Electronics
por: Bhowmik, Sounak, et al.
Publicado: (2024)

QuXAI: Explainers for Hybrid Quantum Machine Learning Models
por: Barua, Saikat, et al.
Publicado: (2025)

A Geometric-Aware Perspective and Beyond: Hybrid Quantum-Classical Machine Learning Methods
por: Alavia, Azadeh, et al.
Publicado: (2025)

Constructing Optimal Noise Channels for Enhanced Robustness in Quantum Machine Learning
por: Winderl, David, et al.
Publicado: (2024)

QuLTSF: Long-Term Time Series Forecasting with Quantum Machine Learning
por: Chittoor, Hari Hara Suthan, et al.
Publicado: (2024)

Quantum Entanglement as Super-Confounding: From Bell's Theorem to Robust Machine Learning
por: Kang, Pilsung
Publicado: (2025)

Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation
por: Hasan, Mohammad Junayed, et al.
Publicado: (2023)

Leveraging Pre-Trained Neural Networks to Enhance Machine Learning with Variational Quantum Circuits
por: Qi, Jun, et al.
Publicado: (2024)

Adiabatic Quantum Support Vector Machines
por: Date, Prasanna, et al.
Publicado: (2024)

Quantum Power Flows: From Theory to Practice
por: Liu, Junyu, et al.
Publicado: (2022)

Beyond MD17: the reactive xxMD dataset
por: Pengmei, Zihan, et al.
Publicado: (2023)

Trustworthy Quantum Machine Learning: A Roadmap for Reliability, Robustness, and Security in the NISQ Era
por: Catak, Ferhat Ozgur, et al.
Publicado: (2025)

Predicting Water Quality using Quantum Machine Learning: The Case of the Umgeni Catchment (U20A) Study Region
por: Khan, Muhammad Al-Zafar, et al.
Publicado: (2024)

Flood Prediction Using Classical and Quantum Machine Learning Models
por: Grzesiak, Marek, et al.
Publicado: (2024)

Transition Role of Entangled Data in Quantum Machine Learning
por: Wang, Xinbiao, et al.
Publicado: (2023)

Infeasibility Aware Large Language Models for Combinatorial Optimization
por: Wang, Yakun, et al.
Publicado: (2026)

Quantum Machine Learning-based 6G edge Network: Enabling Adaptive Communication and Model Aggregation
por: Xiao, Wenjing, et al.
Publicado: (2026)

A Hybrid Quantum-Classical Framework for Financial Volatility Forecasting Based on Quantum Circuit Born Machines
por: Chen, Yixiong
Publicado: (2026)