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 481-492 of 4,265
Evolutionary Discovery of Bivariate Bicycle Codes with LLM-Guided Search
Juan Cruz-Benito, Andrew W. Cross, David Kremer, Ismael Faro
Evolutionary Optimization-Based Design of LQG Controllers in Quantum Coherent Feedback
Chunxiang Song, Yanan Liu, Guofeng Zhang, Huadong Mo, Daoyi Dong
Exact and Asymptotically Complete Robust Verifications of Neural Networks via Quantum Optimization
Wenxin Li, Wenchao Liu, Chuan Wang, Qi Gao, Yin Ma, Hai Wei, Kai Wen
Exchange-Only Silicon Based Spin Qubits: Charge Noise, PINN Optimised Pulse Sequences,and Gate-Level Fidelity
Rajdeep Rameshchandra Dwivedi, Amitoj Singh Miglani, Vishvendra Singh Poonia
Experimental Certification of Ensembles of High-Dimensional Quantum States with Independent Quantum Devices.
Sun YN, Ma MY, Su QP, Sun Z, Yang CP, Nori F.
Experimental data reuploading with provable enhanced learning capabilities.
Mauser MFX, Four S, Predl LM, Albiero R, Ceccarelli F, Osellame R, Petersen P, Dakić B, Agresti I, Walther P
Experimental dipole moment prediction with a progressive 2D-3D hybrid framework and twin-pair-based diagnostic evaluation.
Ugurlu SY, He S
Experimental Implementation of the Quantum Volunteer's Dilemma on NISQ Hardware: Noise Analysis and Digital-Twin Validation
Germán D. Díaz Agreda, Jhon Alejandro Andrade Hoyos, Carlos A. Durán Paredes, Sebastián Cajas Ordoñez, Noah Dane Hebdon, Siong Thye Goh, Dax Enshan Koh
Experimental Side Channel Analysis of Protocol Stages in Quantum Identity Authentication
Marwan Elawady, Lance Young, Contessa Wilburn, Blaine Keyton, Carrie Houston, Mohamed Shaban, Muhammad Ismail
Experimentally Extending Quantum Kernel Learning to Quantum Data by NMR
Vivek Sabarad, Vishal Varma, T. S. Mahesh
Expert evaluation of LLM world models: A high-T(c) superconductivity case study.
Guo H, Tikhanovskaya M, Raccuglia P, Vlaskin A, Co C, Liebling DJ, Ellsworth S, Abraham M, Dorfman E, Armitage NP, Feng C, Georges A, Gingras O, Kiese D, Kivelson SA, Oganesyan V, Ramshaw BJ, Sachdev S, Senthil T, Tranquada JM, Brenner MP, Venugopalan S, Kim EA
Explainable Artificial Intelligence (XAI) and Molecular Modeling Techniques to Discover Putative HER2 Inhibitors.
Rampogu S, Balasubramaniyam T, Yoon CH, Kim Y, Kubiak JZ, Lee KW