Results 71 to 80 of about 2,977,466 (210)

Classification of quantum graphs on M2 and their quantum automorphism groups

Journal of Mathematical Physics, 2022
Motivated by the string diagrammatic approach to undirected tracial quantum graphs by Musto et al. [J. Math. Phys. 59(8), 081706 (2018)], in the former part of this paper, we diagrammatically formulate directed nontracial quantum graphs by Brannan et al. [Commun. Math. Phys. 375(3), 1777 (2019)].
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Universal adversarial perturbations for multiple classification tasks with quantum classifiers

Machine Learning: Science and Technology, 2023
Quantum adversarial machine learning is an emerging field that studies the vulnerability of quantum learning systems against adversarial perturbations and develops possible defense strategies.
Yun-Zhong Qiu
doaj   +1 more source

Quantum autoencoders for image classification

Quantum Machine Intelligence
Classical machine learning often struggles with complex, high-dimensional data. Quantum machine learning offers a potential solution, promising more efficient processing. The quantum convolutional neural network (QCNN), a hybrid algorithm, fits current noisy intermediate-scale quantum hardware.
Hinako Asaoka, Kazue Kudo
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Quantum-inspired classification based on quantum state discrimination [PDF]

Quantum Machine Intelligence
19 pages, 4 ...
Emmanuel Zambrini Cruzeiro, Christine De Mol, Serge Massar, Stefano Pironio   +3 more
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The Search for the Universality Class of Metric Quantum Gravity

, 2021
On the basis of a limited number of reasonable axioms, we discuss the classification of all the possible universality classes of diffeomorphisms invariant metric theories of quantum gravity.
Omar Zanusso, Riccardo Martini, Alessandro Ugolotti   +2 more
core   +1 more source

Quantum phase classification via partial tomography-based quantum hypothesis testing

Scientific Reports
Quantum phase classification is a fundamental problem in quantum many-body physics, traditionally approached using order parameters or quantum machine learning techniques such as quantum convolutional neural networks (QCNNs). However, these methods often
Akira Tanji, Hiroshi Yano, Naoki Yamamoto   +2 more
doaj   +1 more source

Peptide binding classification on quantum computers

Quantum Machine Intelligence
We conduct an extensive study on using near-term quantum computers for a task in the domain of computational biology. By constructing quantum models based on parameterised quantum circuits we perform sequence classification on a task relevant to the design of therapeutic proteins, and find competitive performance with classical baselines of similar ...
Charles London, Douglas Brown, Wenduan Xu, Sezen Vatansever, Christopher James Langmead, Dimitri Kartsaklis, Stephen Clark, Konstantinos Meichanetzidis   +7 more
openaire   +3 more sources

Application of Quantum Pre-Processing Filter for Binary Image Classification with Small Samples [PDF]

Over the past few years, there has been significant interest in Quantum Machine Learning (QML) among researchers, as it has the potential to transform the field of machine learning.
Deo, Ravinesh C., Suzuki, Hajime, Riaz, Farina, Abdulla, Shahab, Ganguly, Srinjoy, Hopkins, Susan   +5 more
core   +1 more source

VSQL: Variational Shadow Quantum Learning for Classification

, 2021
Classification of quantum data is essential for quantum machine learning and near-term quantum technologies. In this paper, we propose a new hybrid quantum-classical framework for supervised quantum learning, which we call Variational Shadow Quantum ...
Wang, X, Li, Guangxi, Wang, Xin, Song, Zhixin, Li, G, Song, Z   +5 more
core   +1 more source

Causal Classification of Spatiotemporal Quantum Correlations

Physical Review Letters
29 ...
Minjeong Song, Varun Narasimhachar, Bartosz Regula, Thomas J. Elliott, Mile Gu   +4 more
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