Quantum Machine Learning
101 papers for year 2019
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 25-36 of 101
Eigenstate extraction with neural-network tomography
Abhijeet Melkani, Clemens Gneiting, Franco Nori
Encrypt me! A game-based approach to Bell inequalities and quantum cryptography
Andrea López-Incera, Andreas Hartmann, Wolfgang Dür
Entaglement-Based Quantum Mean Estimator Circuit
Amanuel Tamirat
Evaluation of the spectrum of a quantum system using machine learning based on incomplete information about the wavefunctions
Gennadiy Burlak
Experimental Measurement of the Hilbert-Schmidt Distance between Two-Qubit States as a Means for Reducing the Complexity of Machine Learning.
Trávníček V, Bartkiewicz K, Černoch A, Lemr K.
Experimental quantum kernel machine learning with nuclear spins in a solid
Takeru Kusumoto, Kosuke Mitarai, Keisuke Fujii, Masahiro Kitagawa, Makoto Negoro
Experimentally attacking quantum money schemes based on quantum retrieval games.
Jiráková K, Bartkiewicz K, Černoch A, Lemr K.
Fairness evaluation during the conceptual design of heat grids with quantum annealers
Kelvin Loh
Gaussian Process Regression Models for the Prediction of Hydrogen Bond Acceptor Strengths.
Bauer CA, Schneider G, Göller AH
Geometry of learning neural quantum states
Chae-Yeun Park, Michael J. Kastoryano
Gossip algorithm with nonuniform clock distribution: Optimization over classical and quantum networks
Saber Jafarizadeh
Hardware-Efficient Quantum Random Access Memory with Hybrid Quantum Acoustic Systems.
Hann CT, Zou CL, Zhang Y, Chu Y, Schoelkopf RJ, Girvin SM, Jiang L.