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 349-360 of 4,265
Decoupling the Dual Impact of NISQ Noise on Quantum Adversarial Robustness
Haoran Wang, Shaoliang Ye, Shaowei Wang, Hanyi Wang, Zhenbo Shi, Wei Yang
Decrypting chaotic visual ciphers via quasi quantum neural networks (Q²NNs).
Manavalan G, Arnon S.
Deep eutectic solvent density prediction: Machine learning from quantum chemical descriptors reveals electronic and stoichiometric controls
Udayakumar Mani, Lavanya Priyadarshini Ramalingam, Senthilkumar Rathinasamy
Deep Learning Approaches to Quantum Error Mitigation
Leonardo Placidi, Ifan Williams, Enrico Rinaldi, Daniel Mills, Cristina Cîrstoiu, Vanya Eccles, Ross Duncan
Deep learning parameter estimation and quantum control of single molecule
Juan M. Scarpetta, Omar Calderón-Losada, Morten Hjorth-Jensen, John H. Reina
Deep learning-based compensation of beam wander and polarization fluctuations for free-space quantum communication
Gibeen Gu, Hyeokin Kang, Taewon Kim, Jeonghun Seong, Young-Jin Kim
Deep Neural Network-Based prediction of electronic and optical properties in CdSe/CdS quantum wells
Adel Bouazra, Safa Maamria
Defending Quantum Classifiers against Adversarial Perturbations through Quantum Autoencoders
Emma Andrews, Sahan Sanjaya, Prabhat Mishra
Demonstrating Coherent Quantum Routers for Bucket-Brigade Quantum Random Access Memory on a Superconducting Processor
Sheng Zhang, Yun-Jie Wang, Peng Wang, Ren-Ze Zhao, Xiao-Yan Yang, Ze-An Zhao, Tian-Le Wang, Hai-Feng Zhang, Zhi-Fei Li, Yuan Wu, Hao-Ran Tao, Liang-Liang Guo, Lei Du, Chi Zhang, Zhi-Long Jia, Wei-Cheng Kong, Zhuo-Zhi Zhang, Xiang-Xiang Song, Yu-Chun Wu, Zhao-Yun Chen, Peng Duan, Guo-Ping Guo
Denoising Diffusion Monte Carlo Electron Densities with Physically Informed Variance Stabilization: From Fourier Filters to 3D UNETs
Kenneth O. Berard, Brenda Rubenstein, Jaron T. Krogel
Density × MA: A Thalamic Model for Raw Qualia as Dynamic Phase Flow
仁定 五十嵐
Derivative Informed Learning of Exchange-Correlation Functionals
Eike S. Eberhard, Luca A. Thiede, Abdul Aldossary, Andreas Burger, Nicholas Gao, Vignesh Bhethanabotla, Alán Aspuru-Guzik, Stephan Günnemann