Quantum Machine Learning
88 papers for year 2018
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 1-12 of 88
64-qubit quantum circuit simulation.
Chen ZY, Zhou Q, Xue C, Yang X, Guo GC, Guo GP.
A belief propagation algorithm based on domain decomposition
Brad Lackey
A Comparison of the Bravyi-Kitaev and Jordan-Wigner Transformations for the Quantum Simulation of Quantum Chemistry.
Tranter A, Love PJ, Mintert F, Coveney PV.
A framework for algorithm deployment on cloud-based quantum computers
Sukin Sim, Yudong Cao, Jonathan Romero, Peter D. Johnson, Alan Aspuru-Guzik
A machine learning approach to the Berezinskii-Kosterlitz-Thouless transition in classical and quantum models
M. Richter-Laskowska, H. Khan, N. Trivedi, M. M. Maśka
A note on the quantum query complexity of permutation symmetric functions
André Chailloux
A quantum homomorphic encryption scheme for polynomial-sized circuits
Li Yu
A Tutorial on Formulating and Using QUBO Models
Fred Glover, Gary Kochenberger, Yu Du
A two-qubit molecular architecture for electron-mediated nuclear quantum simulation.
Atzori M, Chiesa A, Morra E, Chiesa M, Sorace L, Carretta S, Sessoli R.
Adaptive Operator Quantum-Behaved Pigeon-Inspired Optimization Algorithm with Application to UAV Path Planning
Chunhe Hu, Yu Xia, Junguo Zhang
Adaptive Quantum State Tomography with Neural Networks
Yihui Quek, Stanislav Fort, Hui Khoon Ng
Advances in Quantum Reinforcement Learning
Vedran Dunjko, Jacob M. Taylor, Hans J. Briegel