Quantum Machine Learning
3,901 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 1597-1608 of 3,901
Quantum Computing Methods for Malware Detection
Eliška Krátká, Aurél Gábor Gábris
Quantum Computing Standardization and Regulation: Status and Way Forward
Valerio Frascolla
Quantum Computing Systems Implementation and Operations: Technical, Ethical, and National Security Perspectives
Professor of Computer Science and Fellow of the Royal Society Fellow of the British Computer Society (Fellowship, Quantum & Information Security Specialists Committees) American International University West Africa College of Management and Information Technology Kannifing, The Gambia, O. E. Ademola
Quantum Computing–Enabled Clinical Decision Support System using Electronic Health Records and Clinical Documentation
Senthil Kumar T, Srinivasan Rajavelu
Quantum Computing: A Threat to Blockchain Technology and Potential Solutions
R Durga, Department of MBA, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India., Shapash Shaik, Department of Computer Science and Engineering, RK College of Engineering, Vijayawada, Andhra Pradesh India.
Quantum Cryptography and Hardness of Non-Collapsing Measurements
Tomoyuki Morimae, Yuki Shirakawa, Takashi Yamakawa
QUANTUM DECISION-MAKING MODELS IN STRATEGIC MANAGEMENT: NOVEL APPROACH TO HANDLING UNCERTAINTY AND COMPLEX ORGANIZATIONAL BEHAVIOR
Unknown
Quantum Diamond Microscopy for Non-Destructive Failure Analysis of an Integrated Fan-Out Package-on-Package iPhone Chip
Bartu Bisgin, Marwa Garsi, Andreas Welscher, Michael Hanke, Fleming Bruckmaier
Quantum Diplomacy within the Southeast Asia Quantum Ecosystem
Pak Shen Choong, Nurisya Mohd Shah, Yung Szen Yap
Quantum feature encoding optimization
Tommaso Fioravanti, Brian Quanz, Gabriele Agliardi, Edgar Andres Ruiz Guzman, Ginés Carrascal, Jae-Eun Park
Quantum feature-map learning with reduced resource overhead
Jonas Jäger, Philipp Elsässer, Elham Torabian
Quantum Federated Learning: Architectural Elements and Future Directions
Siva Sai, Abhishek Sawaika, Prabhjot Singh, Rajkumar Buyya