Cover Image

Experimental Machine Learning with Classical and Quantum Data via NMR Quantum Kernels

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sabarad, Vivek, Varma, Vishal, Mahesh, T. S.
Format:	Preprint
Published:	2024
Subjects:	Quantum Physics Machine Learning Applied Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Quantum Alternating Operator Ansatz for the Preparation and Detection of Long-Lived Singlet States in NMR
by: Hullamballi, Pratham, et al.
Published: (2024)

TunnElQNN: A Hybrid Quantum-classical Neural Network for Efficient Learning
by: Abbas, A. H.
Published: (2025)

Quantum Machine Learning: Quantum Kernel Methods
by: Naguleswaran, Sanjeev
Published: (2024)

The Quantum Path Kernel: a Generalized Quantum Neural Tangent Kernel for Deep Quantum Machine Learning
by: Incudini, Massimiliano, et al.
Published: (2022)

Distributed and Secure Kernel-Based Quantum Machine Learning
by: Swaminathan, Arjhun, et al.
Published: (2024)

Do Quantum Neural Networks have Simplicity Bias?
by: Pointing, Jessica
Published: (2024)

Benchmarking Quantum Kernel Support Vector Machines Against Classical Baselines on Tabular Data: A Rigorous Empirical Study with Hardware Validation
by: Kakavand, Siavash, et al.
Published: (2026)

Quantum Text Classifier -- A Synchronistic Approach Towards Classical and Quantum Machine Learning
by: Santi, Prabhat, et al.
Published: (2023)

Hybrid Quantum--Classical Machine Learning Potential with Variational Quantum Circuits
by: Willow, Soohaeng Yoo, et al.
Published: (2025)

VQC-MLPNet: An Unconventional Hybrid Quantum-Classical Architecture for Scalable and Robust Quantum Machine Learning
by: Qi, Jun, et al.
Published: (2025)

Hybrid Quantum Neural Network Advantage for Radar-Based Drone Detection and Classification in Low Signal-to-Noise Ratio
by: Malarvanan, Aiswariya Sweety
Published: (2024)

Classical Interfaces for Controlling Cryogenic Quantum Computing Technologies
by: Brennan, Jack C., et al.
Published: (2025)

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

Harnessing Quantum Support Vector Machines for Cross-Domain Classification of Quantum States
by: Sharma, Diksha, et al.
Published: (2024)

Quantum-Classical Machine learning by Hybrid Tensor Networks
by: Liu, Ding, et al.
Published: (2020)

Quantum vs. Classical Machine Learning: A Benchmark Study for Financial Prediction
by: Ahmad, Rehan, et al.
Published: (2026)

Enhancing the Scalability of Classical Surrogates for Real-World Quantum Machine Learning Applications
by: Hernicht, Philip Anton, et al.
Published: (2025)

Non-Unitary Quantum Machine Learning: Fisher Efficiency Transitions from Distributed Quantum Expressivity
by: Masta, Apoorv Kumar, et al.
Published: (2026)

Quantum Kernel Machine Learning for Autonomous Materials Science
by: Adams, Felix, et al.
Published: (2026)

Comparing Latency and Power Consumption: Quantum vs. Classical Preprocessing
by: Amiri, Zuhra, et al.
Published: (2023)

Hybrid Classical-Quantum Transfer Learning with Noisy Quantum Circuits
by: Martín-Pérez, D., et al.
Published: (2026)

Can Entanglement-enhanced Quantum Kernels Improve Data Classification?
by: Babu, Anand, et al.
Published: (2024)

Quantum Machine Learning with HQC Architectures using non-Classically Simulable Feature Maps
by: Ahmad, Syed Farhan, et al.
Published: (2021)

Kernel Learning for Regression via Quantum Annealing Based Spectral Sampling
by: Hasegawa, Yasushi, et al.
Published: (2026)

EnQode: Fast Amplitude Embedding for Quantum Machine Learning Using Classical Data
by: Han, Jason, et al.
Published: (2025)

Position: Quantum Kernel Machines Should Move Beyond Scalar-Valued Kernels to Realize Their Potential
by: Kadri, Hachem, et al.
Published: (2025)

Quantum sensing-enabled deuterium NMR spectroscopy with nanoscale sensitivity at low magnetic fields
by: Singh, Dileep, et al.
Published: (2026)

The Quantum Learning Menagerie (A survey on Quantum learning for Classical concepts)
by: Chatterjee, Sagnik
Published: (2026)

Experimental prime factorization via the feedback quantum control
by: Krishnan, K. B. Hari, et al.
Published: (2026)

Quantum Generator Kernels
by: Altmann, Philipp, et al.
Published: (2026)

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

Enhancing Quantum Support Vector Machines through Variational Kernel Training
by: Innan, Nouhaila, et al.
Published: (2023)

Classical Verification of Quantum Learning Advantages with Noises
by: Ma, Yinghao, et al.
Published: (2024)

Quantum Machine Learning via Contrastive Training
by: Zhukas, Liudmila A., et al.
Published: (2025)

Quantum Data Encoding and Variational Algorithms: A Framework for Hybrid Quantum Classical Machine Learning
by: Bose, Bhavna, et al.
Published: (2025)

Quantum Adversarial Machine Learning and Defense Strategies: Challenges and Opportunities
by: Yocam, Eric, et al.
Published: (2024)

Scalar and Vector Airborne Platform Calibration Using Quantum and Classical Magnetometers and Inertial Sensors
by: Hager, Antonia, et al.
Published: (2026)

Quantum Reinforcement Learning-Guided Diffusion Model for Image Synthesis via Hybrid Quantum-Classical Generative Model Architectures
by: Chen, Chi-Sheng, et al.
Published: (2025)

Hybrid Quantum-Classical Learning for Multiclass Image Classification
by: Anwar, Shuchismita, et al.
Published: (2025)

Benign Overfitting with Quantum Kernels
by: Tomasi, Joachim, et al.
Published: (2025)