Saved in:
| Main Authors: | Yuhan, Jiang, Otten, Matthew |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.10831 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning with SASQuaTCh: a Novel Variational Quantum Transformer Architecture with Kernel-Based Self-Attention
by: Evans, Ethan N., et al.
Published: (2024)
by: Evans, Ethan N., et al.
Published: (2024)
Quantum Kernels for Parity-Structured Classification: A Hybrid Pipeline
by: Pandey, Tushar
Published: (2026)
by: Pandey, Tushar
Published: (2026)
Enhancing Quantum Support Vector Machines through Variational Kernel Training
by: Innan, Nouhaila, et al.
Published: (2023)
by: Innan, Nouhaila, et al.
Published: (2023)
Efficient Parameter Optimisation for Quantum Kernel Alignment: A Sub-sampling Approach in Variational Training
by: Sahin, M. Emre, et al.
Published: (2024)
by: Sahin, M. Emre, et al.
Published: (2024)
Enhancing Small Dataset Classification Using Projected Quantum Kernels with Convolutional Neural Networks
by: Alagiyawanna, A. M. A. S. D., et al.
Published: (2026)
by: Alagiyawanna, A. M. A. S. D., et al.
Published: (2026)
Quantum Generator Kernels
by: Altmann, Philipp, et al.
Published: (2026)
by: Altmann, Philipp, et al.
Published: (2026)
A Resource Efficient Quantum Kernel
by: Singh, Utkarsh, et al.
Published: (2025)
by: Singh, Utkarsh, et al.
Published: (2025)
The Quantum Path Kernel: a Generalized Quantum Neural Tangent Kernel for Deep Quantum Machine Learning
by: Incudini, Massimiliano, et al.
Published: (2022)
by: Incudini, Massimiliano, et al.
Published: (2022)
Benign Overfitting with Quantum Kernels
by: Tomasi, Joachim, et al.
Published: (2025)
by: Tomasi, Joachim, et al.
Published: (2025)
Quantum Machine Learning: Quantum Kernel Methods
by: Naguleswaran, Sanjeev
Published: (2024)
by: Naguleswaran, Sanjeev
Published: (2024)
A Hyperparameter Study for Quantum Kernel Methods
by: Egginger, Sebastian, et al.
Published: (2023)
by: Egginger, Sebastian, et al.
Published: (2023)
QUACK: Quantum Aligned Centroid Kernel
by: Tscharke, Kilian, et al.
Published: (2024)
by: Tscharke, Kilian, et al.
Published: (2024)
Entanglement Detection with Quantum-inspired Kernels and SVMs
by: Martínez-Sabiote, Ana, et al.
Published: (2025)
by: Martínez-Sabiote, Ana, et al.
Published: (2025)
Quantum Variational Activation Functions Empower Kolmogorov-Arnold Networks
by: Jiang, Jiun-Cheng, et al.
Published: (2025)
by: Jiang, Jiun-Cheng, et al.
Published: (2025)
Spectral Phase Encoding for Quantum Kernel Methods
by: Gómez, Pablo Herrero, et al.
Published: (2026)
by: Gómez, Pablo Herrero, et al.
Published: (2026)
Quantum Kernel Methods under Scrutiny: A Benchmarking Study
by: Schnabel, Jan, et al.
Published: (2024)
by: Schnabel, Jan, et al.
Published: (2024)
Position: Quantum Kernel Machines Should Move Beyond Scalar-Valued Kernels to Realize Their Potential
by: Kadri, Hachem, et al.
Published: (2025)
by: Kadri, Hachem, et al.
Published: (2025)
In Search of Quantum Advantage: Estimating the Number of Shots in Quantum Kernel Methods
by: Miroszewski, Artur, et al.
Published: (2024)
by: Miroszewski, Artur, et al.
Published: (2024)
Quantum Policy Gradient in Reproducing Kernel Hilbert Space
by: Bossens, David M., et al.
Published: (2024)
by: Bossens, David M., et al.
Published: (2024)
Distributed and Secure Kernel-Based Quantum Machine Learning
by: Swaminathan, Arjhun, et al.
Published: (2024)
by: Swaminathan, Arjhun, et al.
Published: (2024)
QuaRK: A Quantum Reservoir Kernel for Time Series Learning
by: Aaraba, Abdallah, et al.
Published: (2026)
by: Aaraba, Abdallah, et al.
Published: (2026)
Image Classification with Rotation-Invariant Variational Quantum Circuits
by: Sebastian, Paul San, et al.
Published: (2024)
by: Sebastian, Paul San, et al.
Published: (2024)
Evaluating the Impact of Different Quantum Kernels on the Classification Performance of Support Vector Machine Algorithm: A Medical Dataset Application
by: Akpinar, Emine, et al.
Published: (2024)
by: Akpinar, Emine, et al.
Published: (2024)
Quantum Shadow Gradient Descent for Variational Quantum Algorithms
by: Heidari, Mohsen, et al.
Published: (2023)
by: Heidari, Mohsen, et al.
Published: (2023)
Modeling Quantum Autoencoder Trainable Kernel for IoT Anomaly Detection
by: Chandrasekhar, Swathi, et al.
Published: (2025)
by: Chandrasekhar, Swathi, et al.
Published: (2025)
Resource-Efficient Variational Quantum Classifier
by: Ptáček, Petr, et al.
Published: (2025)
by: Ptáček, Petr, et al.
Published: (2025)
Variational Quantum Optimization with Continuous Bandits
by: Wanner, Marc, et al.
Published: (2025)
by: Wanner, Marc, et al.
Published: (2025)
Barren Plateaus in Variational Quantum Computing
by: Larocca, Martin, et al.
Published: (2024)
by: Larocca, Martin, et al.
Published: (2024)
Experimental Machine Learning with Classical and Quantum Data via NMR Quantum Kernels
by: Sabarad, Vivek, et al.
Published: (2024)
by: Sabarad, Vivek, et al.
Published: (2024)
Quantum Ensemble for Classification
by: Macaluso, Antonio, et al.
Published: (2020)
by: Macaluso, Antonio, et al.
Published: (2020)
Quantum Hierarchical Reinforcement Learning via Variational Quantum Circuits
by: Lee, Yu-Ting, et al.
Published: (2026)
by: Lee, Yu-Ting, et al.
Published: (2026)
Active Learning with Variational Quantum Circuits for Quantum Process Tomography
by: Yang, Jiaqi, et al.
Published: (2024)
by: Yang, Jiaqi, et al.
Published: (2024)
A Quick Introduction to Quantum Machine Learning for Non-Practitioners
by: Evans, Ethan N., et al.
Published: (2024)
by: Evans, Ethan N., et al.
Published: (2024)
Quantum Adversarial Learning for Kernel Methods
by: Montalbano, Giuseppe, et al.
Published: (2024)
by: Montalbano, Giuseppe, et al.
Published: (2024)
Q2SAR: A Quantum Multiple Kernel Learning Approach for Drug Discovery
by: Giraldo, Alejandro, et al.
Published: (2025)
by: Giraldo, Alejandro, et al.
Published: (2025)
Kernel Learning for Regression via Quantum Annealing Based Spectral Sampling
by: Hasegawa, Yasushi, et al.
Published: (2026)
by: Hasegawa, Yasushi, et al.
Published: (2026)
Spectral Bias in Variational Quantum Machine Learning
by: Duffy, Callum, et al.
Published: (2025)
by: Duffy, Callum, et al.
Published: (2025)
Trainability Beyond Linearity in Variational Quantum Objectives
by: Ma, Gordon, et al.
Published: (2026)
by: Ma, Gordon, et al.
Published: (2026)
Warm-Start Variational Quantum Policy Iteration
by: Meyer, Nico, et al.
Published: (2024)
by: Meyer, Nico, et al.
Published: (2024)
Reinforcement Learning for Variational Quantum Circuits Design
by: Foderà, Simone, et al.
Published: (2024)
by: Foderà, Simone, et al.
Published: (2024)
Similar Items
-
Learning with SASQuaTCh: a Novel Variational Quantum Transformer Architecture with Kernel-Based Self-Attention
by: Evans, Ethan N., et al.
Published: (2024) -
Quantum Kernels for Parity-Structured Classification: A Hybrid Pipeline
by: Pandey, Tushar
Published: (2026) -
Enhancing Quantum Support Vector Machines through Variational Kernel Training
by: Innan, Nouhaila, et al.
Published: (2023) -
Efficient Parameter Optimisation for Quantum Kernel Alignment: A Sub-sampling Approach in Variational Training
by: Sahin, M. Emre, et al.
Published: (2024) -
Enhancing Small Dataset Classification Using Projected Quantum Kernels with Convolutional Neural Networks
by: Alagiyawanna, A. M. A. S. D., et al.
Published: (2026)