Cover Image

A Quantum States Preparation Method Based on Difference-Driven Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Wenjie, Xu, Jing, Wang, Bosi
Format:	Preprint
Published:	2023
Subjects:	Quantum Physics Artificial Intelligence Emerging Technologies Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Quantum-Based Feature Selection for Multi-classification Problem in Complex Systems with Edge Computing
by: Liu, Wenjie, et al.
Published: (2023)

A Unitary Weights Based One-Iteration Quantum Perceptron Algorithm for Non-Ideal Training Sets
by: Liu, Wenjie, et al.
Published: (2023)

Component Based Quantum Machine Learning Explainability
by: White, Barra, et al.
Published: (2025)

A quantum system control method based on enhanced reinforcement learning
by: Liu, Wenjie, et al.
Published: (2023)

Quantum Data Center: Perspectives
by: Liu, Junyu, et al.
Published: (2023)

Computable Model-Independent Bounds for Adversarial Quantum Machine Learning
by: Li, Bacui, et al.
Published: (2024)

Variational Quantum Circuits Enhanced Generative Adversarial Network
by: Shu, Runqiu, et al.
Published: (2024)

An Introduction to Quantum Reinforcement Learning (QRL)
by: Chen, Samuel Yen-Chi
Published: (2024)

TensorRL-QAS: Reinforcement learning with tensor networks for improved quantum architecture search
by: Kundu, Akash, et al.
Published: (2025)

KANQAS: Kolmogorov-Arnold Network for Quantum Architecture Search
by: Kundu, Akash, et al.
Published: (2024)

Applying Quantum Autoencoders for Time Series Anomaly Detection
by: Frehner, Robin, et al.
Published: (2024)

Q-fid: Quantum Circuit Fidelity Improvement with LSTM Networks
by: Mao, Yikai, et al.
Published: (2023)

KetGPT - Dataset Augmentation of Quantum Circuits using Transformers
by: Apak, Boran, et al.
Published: (2024)

Implementing Quantum Generative Adversarial Network (qGAN) and QCBM in Finance
by: Ganguly, Santanu
Published: (2023)

Quantum Machine Learning Architecture Search via Deep Reinforcement Learning
by: Dai, Xin, et al.
Published: (2024)

Measuring Accuracy and Energy-to-Solution of Quantum Fine-Tuning of Foundational AI Models
by: Knitter, Oliver, et al.
Published: (2026)

PristiQ: A Co-Design Framework for Preserving Data Security of Quantum Learning in the Cloud
by: Wang, Zhepeng, et al.
Published: (2024)

Breaking QAOA's Fixed Target Hamiltonian Barrier: A Fully Connected Quantum Boltzmann Machine via Bilevel Optimization
by: Liu, Jun
Published: (2026)

Replay-buffer engineering for noise-robust quantum circuit optimization
by: Kundu, Akash, et al.
Published: (2026)

Long Range Frequency Tuning for QML
by: Poppel, Michael, et al.
Published: (2026)

Optimal normalization in quantum-classical hybrid models for anti-cancer drug response prediction
by: Ito, Takafumi, et al.
Published: (2025)

Compiler Optimization for Quantum Computing Using Reinforcement Learning
by: Quetschlich, Nils, et al.
Published: (2022)

QuEst: Graph Transformer for Quantum Circuit Reliability Estimation
by: Wang, Hanrui, et al.
Published: (2022)

Introduction to Quantum Machine Learning and Quantum Architecture Search
by: Chen, Samuel Yen-Chi, et al.
Published: (2025)

Learning to Program Quantum Measurements for Machine Learning
by: Chen, Samuel Yen-Chi, et al.
Published: (2025)

Learning to Measure Quantum Neural Networks
by: Chen, Samuel Yen-Chi, et al.
Published: (2025)

Adversarial Robustness of Partitioned Quantum Classifiers
by: Kananian, Pouya, et al.
Published: (2025)

Enhancing Quantum Federated Learning with Fisher Information-Based Optimization
by: Bhatia, Amandeep Singh, et al.
Published: (2025)

Learning to Program Variational Quantum Circuits with Fast Weights
by: Chen, Samuel Yen-Chi
Published: (2024)

Quantum Circuit Synthesis and Compilation Optimization: Overview and Prospects
by: Yan, Ge, et al.
Published: (2024)

Differentiable Quantum Architecture Search in Quantum-Enhanced Neural Network Parameter Generation
by: Chen, Samuel Yen-Chi, et al.
Published: (2025)

Quantum Kernel Learning for Small Dataset Modeling in Semiconductor Fabrication: Application to Ohmic Contact
by: Wang, Zeheng, et al.
Published: (2024)

Analyzing Images of Blood Cells with Quantum Machine Learning Methods: Equilibrium Propagation and Variational Quantum Circuits to Detect Acute Myeloid Leukemia
by: Bano, A., et al.
Published: (2026)

Solving Drone Routing Problems with Quantum Computing: A Hybrid Approach Combining Quantum Annealing and Gate-Based Paradigms
by: Osaba, Eneko, et al.
Published: (2025)

A hybrid quantum-classical conditional generative adversarial network algorithm for human-centered paradigm in cloud
by: Liu, Wenjie, et al.
Published: (2023)

Addressing the Minor-Embedding Problem in Quantum Annealing and Evaluating State-of-the-Art Algorithm Performance
by: Gomez-Tejedor, Aitor, et al.
Published: (2025)

Transformer-Based Neural Quantum Digital Twins for Many-Body Quantum Simulation and Optimal Annealing Schedule Design
by: Lu, Jianlong, et al.
Published: (2025)

Quantum Machine Learning in Precision Medicine and Drug Discovery -- A Game Changer for Tailored Treatments?
by: Bertl, Markus, et al.
Published: (2025)

Quantum Long Short-term Memory with Differentiable Architecture Search
by: Chen, Samuel Yen-Chi, et al.
Published: (2025)

Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacity
by: Chen, Samuel Yen-Chi
Published: (2024)