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 2137-2148 of 4,297
Variational quantum generative modeling by sampling expectation values of tunable observables.
Shen K, Kurkin A, Pérez-Salinas A, Shishenina E, Dunjko V, Wang H.
Variational Quantum Integrated Sensing and Communication
Ivana Nikoloska, Osvaldo Simeone
Variational Quantum RNS Comparator: A Cluster-Inspired Quantum Machine Learning Architecture for Residue Number Systems
Ghayour P.
Vehicle Routing Problems via Quantum Graph Attention Network Deep Reinforcement Learning
Le Tung Giang, Vu Hoang Viet, Nguyen Xuan Tung, Trinh Van Chien, Won-Joo Hwang
Wavefunction Flows: Efficient Quantum Simulation of Continuous Flow Models
David Layden, Ryan Sweke, Vojtěch Havlíček, Anirban Chowdhury, Kirill Neklyudov
Wavelength-Based Quantum Coding in Vision and Hearing: A Comparative Analysis of Neural Processing Architectures
Ravinder Jerath, Varsha Malani
What is Stochastic Supervenience?
Youheng Zhang
When Abstraction Breaks Physics: Rethinking Modular Design in Quantum Software
Jianjun Zhao
$i$Trust: Trust-Region Optimisation with Ising Machines
Sayantan Pramanik, Kaumudibikash Goswami, Sourav Chatterjee, M Girish Chandra
A Brief Review of Quantum Machine Learning for Financial Services
Mina Doosti, Petros Wallden, Conor Brian Hamill, Robert Hankache, Oliver Thomson Brown, Chris Heunen
A Case for Quantum Circuit Cutting for NISQ Applications: Impact of topology, determinism, and sparsity
Zirui Li, Minghao Guo, Mayank Barad, Wei Tang, Eddy Z. Zhang, Yipeng Huang
A Comprehensive Review of Quantum Circuit Optimization: Current Trends and Future Directions
Krishnageetha Karuppasamy, Varun Puram, Stevens Johnson, Johnson P Thomas