Quantum Machine Learning
3,901 papers
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 3217-3228 of 3,901
Bilinear dynamic mode decomposition for quantum control
Andy Goldschmidt, Eurika Kaiser, Jonathan L. Dubois, Steven L. Brunton, J. Nathan Kutz
Bootstrapping quantum process tomography via a perturbative ansatz.
Govia LCG, Ribeill GJ, Ristè D, Ware M, Krovi H.
Chaos and Complexity from Quantum Neural Network: A study with Diffusion Metric in Machine Learning
Sayantan Choudhury, Ankan Dutta, Debisree Ray
Characterizing the loss landscape of variational quantum circuits
Patrick Huembeli, Alexandre Dauphin
Circuit-based quantum random access memory for classical data with continuous amplitudes
Tiago M. L. de Veras, Ismael C. S. de Araujo, Daniel K. Park, Adenilton J. da Silva
Classical and quantum random-walk centrality measures in multilayer networks
Lucas Böttcher, Mason A. Porter
Classical symmetries and the Quantum Approximate Optimization Algorithm
Ruslan Shaydulin, Stuart Hadfield, Tad Hogg, Ilya Safro
Comment on 'Semi-Quantum Private Comparison Based on Bell States'
You-Lin Chen, Yu-Chin Lu, Zhong-Xuan Lin, Tzonelih Hwang
Comparative study of variational quantum circuit and quantum backpropagation multilayer perceptron for COVID-19 outbreak predictions
Pranav Kairon, Siddhartha Bhattacharyya
Compiling quantamorphisms for the IBM Q Experience
Ana Neri, Rui Soares Barbosa, José N. Oliveira
Complex Paths Around The Sign Problem
Andrei Alexandru, Gokce Basar, Paulo F. Bedaque, Neill C. Warrington
Constant-round Blind Classical Verification of Quantum Sampling
Kai-Min Chung, Yi Lee, Han-Hsuan Lin, Xiaodi Wu