Image de couverture de livre

Reinforcement Learning for Variational Quantum Circuits Design

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Foderà, Simone, Turati, Gloria, Nembrini, Riccardo, Dacrema, Maurizio Ferrari, Cremonesi, Paolo
Format:	Preprint
Publié:	2024
Sujets:	Quantum Physics Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Separating Ansatz Discovery from Deployment on Larger Problems: Reinforcement Learning for Modular Circuit Design
par: Turati, Gloria, et autres
Publié: (2025)

Minor Embedding for Quantum Annealing with Reinforcement Learning
par: Nembrini, Riccardo, et autres
Publié: (2025)

Benchmarking Adaptative Variational Quantum Algorithms on QUBO Instances
par: Turati, Gloria, et autres
Publié: (2023)

An Empirical Analysis on the Effectiveness of the Variational Quantum Linear Solver
par: Turati, Gloria, et autres
Publié: (2024)

Adaptive Learning for Quantum Linear Regression
par: Carugno, Costantino, et autres
Publié: (2024)

Hamiltonian Expressibility for Ansatz Selection in Variational Quantum Algorithms
par: Brozzi, Filippo, et autres
Publié: (2025)

Analyzing the Effectiveness of Quantum Annealing with Meta-Learning
par: Pellini, Riccardo, et autres
Publié: (2024)

Quantum Approaches to Urban Logistics: From Core QAOA to Clustered Scalability
par: Picariello, F., et autres
Publié: (2025)

Comment on arXiv:2307.08384 "Efficient Quantum State Preparation with Walsh Series"
par: Pellini, Riccardo, et autres
Publié: (2025)

An Evaluation Study of Generative Adversarial Networks for Collaborative Filtering
par: Maurera, Fernando Benjamín Pérez, et autres
Publié: (2022)

Quantum Hierarchical Reinforcement Learning via Variational Quantum Circuits
par: Lee, Yu-Ting, et autres
Publié: (2026)

Challenges for Reinforcement Learning in Quantum Circuit Design
par: Altmann, Philipp, et autres
Publié: (2023)

Breaking Through Barren Plateaus: Reinforcement Learning Initializations for Deep Variational Quantum Circuits
par: Peng, Yifeng, et autres
Publié: (2025)

Impression-Aware Recommender Systems
par: Maurera, Fernando B. Pérez, et autres
Publié: (2023)

Optimizing Variational Quantum Circuits Using Metaheuristic Strategies in Reinforcement Learning
par: Kölle, Michael, et autres
Publié: (2024)

A Study on Optimization Techniques for Variational Quantum Circuits in Reinforcement Learning
par: Kölle, Michael, et autres
Publié: (2024)

Active Learning with Variational Quantum Circuits for Quantum Process Tomography
par: Yang, Jiaqi, et autres
Publié: (2024)

Physics-Informed Bayesian Optimization of Variational Quantum Circuits
par: Nicoli, Kim A., et autres
Publié: (2024)

Fourier Analysis of Variational Quantum Circuits for Supervised Learning
par: Wiedmann, Marco, et autres
Publié: (2024)

Equivariant Reinforcement Learning for Clifford Quantum Circuit Synthesis
par: Yeung, Richie, et autres
Publié: (2026)

Transfer Learning Analysis of Variational Quantum Circuits
par: Tseng, Huan-Hsin, et autres
Publié: (2025)

Variational Quantum Circuit-Based Reinforcement Learning for Dynamic Portfolio Optimization
par: Gurgul, Vincent, et autres
Publié: (2026)

Beyond Reinforcement Learning: Fast and Scalable Quantum Circuit Synthesis
par: Theißinger, Lukas, et autres
Publié: (2026)

Reinforcement Learning for Adaptive Composition of Quantum Circuit Optimisation Passes
par: Mills, Daniel, et autres
Publié: (2026)

Enhancing the Trainability of Variational Quantum Circuits with Regularization Strategies
par: Zhuang, Jun, et autres
Publié: (2024)

Special-Unitary Parameterization for Trainable Variational Quantum Circuits
par: Chen, Kuan-Cheng, et autres
Publié: (2025)

Pre-training Tensor-Train Networks Facilitates Machine Learning with Variational Quantum Circuits
par: Qi, Jun, et autres
Publié: (2023)

Hybrid Quantum--Classical Machine Learning Potential with Variational Quantum Circuits
par: Willow, Soohaeng Yoo, et autres
Publié: (2025)

Qubit-Wise Architecture Search Method for Variational Quantum Circuits
par: Chen, Jialin, et autres
Publié: (2024)

Formal Verification of Variational Quantum Circuits
par: Assolini, Nicola, et autres
Publié: (2025)

QAdaPrune: Adaptive Parameter Pruning For Training Variational Quantum Circuits
par: Kulshrestha, Ankit, et autres
Publié: (2024)

Investigating and Mitigating Barren Plateaus in Variational Quantum Circuits: A Survey
par: Cunningham, Jack, et autres
Publié: (2024)

Investigation of Automated Design of Quantum Circuits for Imaginary Time Evolution Methods Using Deep Reinforcement Learning
par: Suzuki, Ryo, et autres
Publié: (2026)

Optimizing Quantum Circuits via ZX Diagrams using Reinforcement Learning and Graph Neural Networks
par: Mattick, Alexander, et autres
Publié: (2025)

QCA-MolGAN: Quantum Circuit Associative Molecular GAN with Multi-Agent Reinforcement Learning
par: Thomas, Aaron Mark, et autres
Publié: (2025)

Scalable Quantum Reinforcement Learning on NISQ Devices with Dynamic-Circuit Qubit Reuse and Grover Optimization
par: Su, Thet Htar, et autres
Publié: (2025)

Investigating the Lottery Ticket Hypothesis for Variational Quantum Circuits
par: Kölle, Michael, et autres
Publié: (2025)

Automated Off-Policy Estimator Selection via Supervised Learning
par: Felicioni, Nicolò, et autres
Publié: (2024)

Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits
par: Zhang, Kaining, et autres
Publié: (2022)

Hybrid Reward-Driven Reinforcement Learning for Efficient Quantum Circuit Synthesis
par: Giordano, Sara, et autres
Publié: (2025)