Quantum Machine Learning
4,265 papers
Quantum Machine Learning Research Context
This category covers quantum machine learning research, including quantum kernels, variational classifiers, hybrid learning systems, generative models, and QML benchmarks.
Showing 553-564 of 4,265
From Characterization To Construction: Generative Quantum Circuit Synthesis from Gate Set Tomography Data
King Yiu Yu, Aritra Sarkar, Erbing Hua, Maximilian Rimbach-Russ, Ryoichi Ishihara, Sebastian Feld
From Classical to Quantum Reinforcement Learning and Its Applications in Quantum Control: A Beginner's Tutorial
Abhijit Sen, Sonali Panda, Mahima Arya, Subhajit Patra, Zizhan Zheng, Denys I. Bondar
From data to diagnosis: A comprehensive review of machine learning-driven wearable sensors in healthcare.
Zhao M, Liu R, Jin S, Ren B, Zhang Q
From Foundation ECG Models to NISQ Learners: Distilling ECGFounder into a VQC Student
Giovanni dos Santos Franco, Felipe Mahlow, Ellison Fernando Cardoso, Felipe Fanchini
From hyperplanes to hyperellipsoids: characterizing the inherent interpretability of linear and single-qubit mixed-state binary classification models
Kaitlin Gili
From intuition to optimization: a review of inverse design applied to optical nanotweezers.
Nelson D, Kim S, Crozier KB
From membership-privacy leakage to quantum machine unlearning
Junjian Su, Runze He, Guanghui Li, Sujuan Qin, Zhimin He, Haozhen Situ, Fei Gao
From Reachability to Learnability: Geometric Design Principles for Quantum Neural Networks
Vishal S. Ngairangbam, Michael Spannowsky
From Tensor Networks to Tractable Circuits, and back
Arend-Jan Quist, Marc Farreras Bartra, Alexis de Colnet, John van de Wetering, Alfons Laarman
From vacuum amplitudes to qubits
Germán Rodrigo
Fundamental questions on robustness and accuracy for classical and quantum learning algorithms
Nana Liu
Fundamentals of Quantum Machine Learning and Robustness
Lirandë Pira, Patrick Rebentrost