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 193-204 of 237
Sample optimal Quantum identity testing via Pauli Measurements
Nengkun Yu
Scientific intuition inspired by machine learning generated hypotheses
Pascal Friederich, Mario Krenn, Isaac Tamblyn, Alan Aspuru-Guzik
Scrambling Ability of Quantum Neural Networks Architectures
Yadong Wu, Pengfei Zhang, Hui Zhai
Sensitive magnetometry in challenging environments
Kai-Mei C. Fu, Geoffrey Z. Iwata, Arne Wickenbrock, Dmitry Budker
Simultaneous Quantum Machine Learning Training and Architecture Discovery
Dominic Pasquali
Single-Photon Image Classification
Thomas Fischbacher, Luciano Sbaiz
Single-Pixel Pattern Recognition with Coherent Nonlinear Optics
Ting Bu, Santosh Kumar, He Zhang, Irwin Huang, Yuping Huang
Software Pipelining for Quantum Loop Programs
Jingzhe Guo, Mingsheng Ying
Solving Quasiparticle Band Spectra of Real Solids using Neural-Network Quantum States
Nobuyuki Yoshioka, Wataru Mizukami, Franco Nori
Spin-photon module for scalable network architecture in quantum dots.
Zhu XY, Tu T, Guo AL, Zhou ZQ, Guo GC, Li CF.
Sublinear classical and quantum algorithms for general matrix games
Tongyang Li, Chunhao Wang, Shouvanik Chakrabarti, Xiaodi Wu
Supervised Learning Using a Dressed Quantum Network with "Super Compressed Encoding": Algorithm and Quantum-Hardware-Based Implementation
Saurabh Kumar, Siddharth Dangwal, Debanjan Bhowmik