Quantum Machine Learning
248 papers for year 2022
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 85-96 of 248
Game Changer in Cybersecurity: Quantum Cryptography
Amitabh VERMA
General Classification of Entanglement Using Machine Learning
F. El Ayachi, M. El Baz
Generalization despite overfitting in quantum machine learning models
Evan Peters, Maria Schuld
Generating Approximate Ground States of Molecules Using Quantum Machine Learning
Jack Ceroni, Torin F. Stetina, Maria Kieferova, Carlos Ortiz Marrero, Juan Miguel Arrazola, Nathan Wiebe
Generative model for learning quantum ensemble via optimal transport loss
Hiroyuki Tezuka, Shumpei Uno, Naoki Yamamoto
Gibbs Sampling of Continuous Potentials on a Quantum Computer
Arsalan Motamedi, Pooya Ronagh
Glutathione-Capped CdTe Quantum Dots Based Sensors for Detection of H2O2 and Enrofloxacin in Foods Samples
Shijie Li, Linqing Nie, Lin Han, Wenjun Wen, Junping Wang, Shuo Wang
Google's Quantum Supremacy Claim: Data, Documentation, and Discussion
Gil Kalai, Yosef Rinott, Tomer Shoham
Gradient Estimation with Constant Scaling for Hybrid Quantum Machine Learning
Thomas Hoffmann, Douglas Brown
HCQC: Hybrid Classical -Quantum -Classical Transfer Learning Method for COVID-19 Detection
Rao GVE, B R, Chalumuri A, Shukla M.
Hierarchical quantum circuit representations for neural architecture search
Matt Lourens, Ilya Sinayskiy, Daniel K. Park, Carsten Blank, Francesco Petruccione
High-performance state-vector emulator of a gate-based quantum processor implemented in the Rust programming language
Ilya A. Luchnikov, Oleg E. Tatarkin, Aleksey K. Fedorov