Quantum Machine Learning
237 papers for year 2020
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 237
A Computer Science-Oriented Approach to Introduce Quantum Computing to a New Audience
Özlem Salehi, Zeki Seskir, İlknur Tepe
A divide-and-conquer algorithm for quantum state preparation
Israel F. Araujo, Daniel K. Park, Francesco Petruccione, Adenilton J. da Silva
A heterometallic [LnLn'Ln] lanthanide complex as a qubit with embedded quantum error correction.
Macaluso E, Rubín M, Aguilà D, Chiesa A, Barrios LA, Martínez JI, Alonso PJ, Roubeau O, Luis F, Aromí G, Carretta S.
A Hybrid Framework Using a QUBO Solver For Permutation-Based Combinatorial Optimization
Siong Thye Goh, Sabrish Gopalakrishnan, Jianyuan Bo, Hoong Chuin Lau
A new state of matter of quantum droplets
Mingyang Guo, Tilman Pfau
A non-algorithmic approach to "programming" quantum computers via machine learning
Nathan Thompson, James Steck, Elizabeth Behrman
A P4 Data Plane for the Quantum Internet
Wojciech Kozlowski, Fernando Kuipers, Stephanie Wehner
A Quantum Graph Neural Network Approach to Particle Track Reconstruction
Cenk Tüysüz, Federico Carminati, Bilge Demirköz, Daniel Dobos, Fabio Fracas, Kristiane Novotny, Karolos Potamianos, Sofia Vallecorsa, Jean-Roch Vlimant
A Query-Efficient Quantum Algorithm for Maximum Matching on General Graphs
Shelby Kimmel, R. Teal Witter
A rigorous and robust quantum speed-up in supervised machine learning
Yunchao Liu, Srinivasan Arunachalam, Kristan Temme
A Tutorial Introduction to Quantum Circuit Programming in Dependently Typed Proto-Quipper
Fu P, Kishida K, Ross N, Selinger P.
A Tutorial on Quantum Convolutional Neural Networks (QCNN)
Seunghyeok Oh, Jaeho Choi, Joongheon Kim