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 73-84 of 237
General error mitigation for quantum circuits
Manpreet Singh Jattana, Fengping Jin, Hans De Raedt, Kristel Michielsen
Generation of High-Resolution Handwritten Digits with an Ion-Trap Quantum Computer
Manuel S. Rudolph, Ntwali Bashige Toussaint, Amara Katabarwa, Sonika Johri, Borja Peropadre, Alejandro Perdomo-Ortiz
Generative machine learning with tensor networks: benchmarks on near-term quantum computers
Michael L. Wall, Matthew R. Abernathy, Gregory Quiroz
Global Optimum Search in Quantum Deep Learning
Lanston Hau Man Chu, Tejas Bhojraj, Rui Huang
Graph Coloring with Quantum Annealing
Julia Kwok, Kristen Pudenz
High-speed computational ghost imaging with compressed sensing based on a convolutional neural network
Hao Zhang, Deyang Duan
High-Throughput Calculations for High-Entropy Alloys: A Brief Review
Ruixuan Li, Lu Xie, William Yi Wang, Peter K. Liaw, Yong Zhang, Yong Zhang
Homomorphic Encryption for Quantum Annealing with Spin Reversal Transformations
Daniel O'Malley, John K. Golden
How a Quantum Computer Could Solve a Microkinetic Model
Eric A. Walker, Shreyas Addamane Pallathadka
How to enhance quantum generative adversarial learning of noisy information
Paolo Braccia, Filippo Caruso, Leonardo Banchi
Hybrid quantum-classical classifier based on tensor network and variational quantum circuit
Samuel Yen-Chi Chen, Chih-Min Huang, Chia-Wei Hsing, Ying-Jer Kao
Hybrid quantum-classical unsupervised data clustering based on the self-organizing feature map
Ilia D. Lazarev, Marek Narozniak, Tim Byrnes, Alexey N. Pyrkov