Quantum Machine Learning
4,297 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 85-96 of 4,297
A saturation-absorption rubidium magnetometer with multilevel optical Bloch-equation modeling for intermediate-to-high fields
Mayand Dangi, Prateek Rajan Gupta, Joseph Kasti, Nivedan Vishwanath, Michael Zepp, David Smith, Benedikt Geiger, Jennifer T. Choy
A Security-Aware Nonlinearity Study of FPGA-Based Time-to-Digital Converters for Quantum Key Distribution Systems
Kun Qin, Carsten Trinitis
A Semantic Quantum Circuit Cache for Scalable and Distributed Quantum-Classical Workflows
Mar Tejedor, Javier Conejero, Rosa M. Badia
A single design choice determines whether machine learning models of materials make physically impossible predictions
Can Polat, Mustafa Kurban, Erchin Serpedin, Hasan Kurban
A Specialized Importance-Aware Quantum Convolutional Neural Network with Ring-Topology (IA-QCNN) for MGMT Promoter Methylation Prediction in Glioblastoma
Emine Akpinar, Murat Oduncuoglu
A Survey on Applications of Quantum Computing for Unit Commitment
Milad Hasanzadeh, Ali Rajabi, Amin Kargarian
A systematic exploration of quantum software engineering in the NISQ era: Methods, lifecycle practices, and a taxonomy of challenges
Mir Mohammad Yousuf, Shabir Ahmad Sofi
A systematic literature review of quantum machine learning for medical: trends, datasets, topics, and methods
Agustinus Eko Setiawan, Supriadi Rustad, Abdul Syukur, Moch Arief Soeleman, Guruh Fajar Shidik, Ifran Lindu Mahargya, Muhamad Akrom, Andreas Wilson Setiawan
A Systematic Literature Review on Modern Cryptographic and Authentication Schemes for Securing the Internet of Things
Tehseen Hussain, Fraz Ahmad, Dr. Zia Ur Rehman
A Systematic Study of Noise Effects in Hybrid Quantum-Classical Machine Learning
Bhavna Bose, Muhammad Faryad
A Theory of Finite-Noise Optima and Generalization in Quantum Machine Learning
Ziyu Zhang, Zikang Jia, Xiaosong Li, Yulong Dong
A Transferable Machine Learning Approach to Predict Optimized Orbitals for Electronic Structure Problems
Lucas van der Horst, Maniraman Periyasamy, Abhishek Y. Dubey, Davide Bincoletto, Jakob S. Kottmann, Daniel D. Scherer