Quantum Machine Learning
11 papers for year 2017 from Europe PMC
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 1-11 of 11
Application of optimal band-limited control protocols to quantum noise sensing.
Frey VM, Mavadia S, Norris LM, de Ferranti W, Lucarelli D, Viola L, Biercuk MJ.
Basic protocols in quantum reinforcement learning with superconducting circuits.
Lamata L.
Deep Neural Network Probabilistic Decoder for Stabilizer Codes.
Krastanov S, Jiang L.
Dissipative quantum error correction and application to quantum sensing with trapped ions.
Reiter F, Sørensen AS, Zoller P, Muschik CA.
Experimental comparison of two quantum computing architectures.
Linke NM, Maslov D, Roetteler M, Debnath S, Figgatt C, Landsman KA, Wright K, Monroe C.
Experimental demonstration of a fully inseparable quantum state with nonlocalizable entanglement.
Mičuda M, Koutný D, Miková M, Straka I, Ježek M, Mišta L.
Experimental Detection of Quantum Channel Capacities.
Cuevas Á, Proietti M, Ciampini MA, Duranti S, Mataloni P, Sacchi MF, Macchiavello C.
Fault-tolerant quantum error detection.
Linke NM, Gutierrez M, Landsman KA, Figgatt C, Debnath S, Brown KR, Monroe C.
Hardware for dynamic quantum computing.
Ryan CA, Johnson BR, Ristè D, Donovan B, Ohki TA.
Prediction and real-time compensation of qubit decoherence via machine learning.
Mavadia S, Frey V, Sastrawan J, Dona S, Biercuk MJ.
Reaching Agreement in Quantum Hybrid Networks.
Shi G, Li B, Miao Z, Dower PM, James MR.