{"total":43,"rows":[{"id":"2111.05292","title":"Generalization in quantum machine learning from few training data","created":"2021-11-09","cited_by_count":216,"area":null},{"id":"2106.03747","title":"The Inductive Bias of Quantum Kernels","created":"2021-06-07","cited_by_count":91,"area":null},{"id":"2208.11060","title":"Exponential concentration in quantum kernel methods","created":"2022-08-23","cited_by_count":90,"area":null},{"id":"2105.02276","title":"Training Quantum Embedding Kernels on Near-Term Quantum Computers","created":"2021-05-05","cited_by_count":69,"area":null},{"id":"2108.13421","title":"Recent advances for quantum classifiers","created":"2021-08-30","cited_by_count":35,"area":null},{"id":"2206.06686","title":"Bandwidth Enables Generalization in Quantum Kernel Models","created":"2022-06-14","cited_by_count":32,"area":null},{"id":"2401.11351","title":"A comprehensive review of Quantum Machine Learning: from NISQ to Fault Tolerance","created":"2024-01-21","cited_by_count":32,"area":null},{"id":"2308.13422","title":"QKSAN: A Quantum Kernel Self-Attention Network","created":"2023-08-25","cited_by_count":23,"area":null},{"id":"2106.04975","title":"The dilemma of quantum neural networks","created":"2021-06-09","cited_by_count":20,"area":null},{"id":"2301.01597","title":"Problem-Dependent Power of Quantum Neural Networks on Multi-Class Classification","created":"2022-12-29","cited_by_count":20,"area":null},{"id":"2112.06211","title":"Quantum kernels for real-world predictions based on electronic health records","created":"2021-12-12","cited_by_count":15,"area":null},{"id":"2307.00908","title":"Quantum Machine Learning on Near-Term Quantum Devices: Current State of Supervised and Unsupervised Techniques for Real-World Applications","created":"2023-07-03","cited_by_count":14,"area":null},{"id":"2206.02806","title":"Quantum Neural Network Classifiers: A Tutorial","created":"2022-06-06","cited_by_count":13,"area":null},{"id":"2401.09393","title":"\\'Eliv\\'agar: Efficient Quantum Circuit Search for Classification","created":"2024-01-17","cited_by_count":12,"area":null},{"id":"2511.15969","title":"A Primer on Quantum Machine Learning","created":"2025-11-20","cited_by_count":12,"area":null},{"id":"2107.05224","title":"Fock State-enhanced Expressivity of Quantum Machine Learning Models","created":"2021-07-12","cited_by_count":11,"area":null},{"id":"2206.15284","title":"Quantum Advantage Seeker with Kernels (QuASK): a software framework to speed up the research in quantum machine learning","created":"2022-06-30","cited_by_count":11,"area":null},{"id":"2304.12923","title":"Quantum Gaussian Process Regression for Bayesian Optimization","created":"2023-04-25","cited_by_count":9,"area":null},{"id":"2109.04298","title":"Quantum Machine Learning for Finance","created":"2021-09-09","cited_by_count":7,"area":null},{"id":"2210.02355","title":"A kernel-based quantum random forest for improved classification","created":"2022-10-05","cited_by_count":7,"area":null},{"id":"2401.11098","title":"Neural auto-designer for enhanced quantum kernels","created":"2024-01-20","cited_by_count":7,"area":null},{"id":"2409.07626","title":"Generalization Error Bound for Quantum Machine Learning in NISQ Era -- A Survey","created":"2024-09-11","cited_by_count":7,"area":null},{"id":"2106.15432","title":"On exploring the potential of quantum auto-encoder for learning quantum systems","created":"2021-06-29","cited_by_count":6,"area":null},{"id":"2204.06904","title":"Efficient and practical quantum compiler towards multi-qubit systems with deep reinforcement learning","created":"2022-04-14","cited_by_count":6,"area":null},{"id":"2205.04730","title":"Power of Quantum Generative Learning","created":"2022-05-10","cited_by_count":6,"area":null},{"id":"2306.03481","title":"Transition Role of Entangled Data in Quantum Machine Learning","created":"2023-06-06","cited_by_count":5,"area":null},{"id":"2106.12819","title":"Accelerating variational quantum algorithms with multiple quantum processors","created":"2021-06-24","cited_by_count":4,"area":null},{"id":"2309.10441","title":"Coreset selection can accelerate quantum machine learning models with provable generalization","created":"2023-09-19","cited_by_count":4,"area":null},{"id":"2505.20337","title":"Predictive Performance of Deep Quantum Data Re-uploading Models","created":"2025-05-24","cited_by_count":4,"area":null},{"id":"2210.06971","title":"Shot-frugal and Robust quantum kernel classifiers","created":"2022-10-13","cited_by_count":3,"area":null},{"id":"2311.08990","title":"sQUlearn -- A Python Library for Quantum Machine Learning","created":"2023-11-15","cited_by_count":3,"area":null},{"id":"2505.08782","title":"Addressing the Current Challenges of Quantum Machine Learning through Multi-Chip Ensembles","created":"2025-05-13","cited_by_count":3,"area":null},{"id":"2404.07330","title":"A Modified Depolarization Approach for Efficient Quantum Machine Learning","created":"2024-04-10","cited_by_count":2,"area":null},{"id":"2508.15230","title":"Robust and Efficient Quantum Reservoir Computing with Discrete Time Crystal","created":"2025-08-21","cited_by_count":2,"area":null},{"id":"2604.07896","title":"Non-variational supervised quantum kernel methods: a review","created":"2026-04-09","cited_by_count":2,"area":null},{"id":"2405.07226","title":"Separable Power of Classical and Quantum Learning Protocols Through the Lens of No-Free-Lunch Theorem","created":"2024-05-12","cited_by_count":1,"area":null},{"id":"2409.07632","title":"Learning Robust Observable to Address Noise in Quantum Machine Learning","created":"2024-09-11","cited_by_count":1,"area":null},{"id":"2506.03779","title":"Position: Quantum Kernel Machines Should Move Beyond Scalar-Valued Kernels to Realize Their Potential","created":"2025-06-04","cited_by_count":1,"area":null},{"id":"2508.07104","title":"QuProFS: An Evolutionary Training-free Approach to Efficient Quantum Feature Map Search","created":"2025-08-09","cited_by_count":1,"area":null},{"id":"2602.00048","title":"Quantum Circuit-Based Learning Models: Bridging Quantum Computing and Machine Learning","created":"2026-01-19","cited_by_count":1,"area":null},{"id":"2505.24765","title":"Supervised Quantum Machine Learning: A Future Outlook from Qubits to Enterprise Applications","created":"2025-05-30","cited_by_count":0,"area":null},{"id":"2512.11367","title":"Maritime object classification with SAR imagery using quantum kernel methods","created":"2025-12-12","cited_by_count":0,"area":null},{"id":"2607.20377","title":"Statevector-to-Hardware Reconstruction of a Four-Qubit ZZ Quantum Kernel: A Single-Backend Case Study of Three Execution Jobs","created":"2026-07-22","cited_by_count":0,"area":null}],"next_cursor":null}