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Publication search results
found 218 matches
- 2024
- Ohad Amosy, Tamuz Danzig, Ohad Lev, Ely Porat, Gal Chechik, Adi Makmal:
Iteration-Free quantum approximate optimization algorithm using neural networks. Quantum Mach. Intell. 6(2): 38 (2024) - Ebrahim Ardeshir-Larijani, Mohammad Mahdi Nasiri Fatmehsari:
Hybrid classical-quantum transfer learning for text classification. Quantum Mach. Intell. 6(1): 19 (2024) - Marco Baioletti, Francesco Santini:
An encoding of argumentation problems using quadratic unconstrained binary optimization. Quantum Mach. Intell. 6(2): 51 (2024) - Jack S. Baker, Gilchan Park, Kwangmin Yu, Ara Ghukasyan, Oktay Göktas, Santosh Kumar Radha:
Parallel hybrid quantum-classical machine learning for kernelized time-series classification. Quantum Mach. Intell. 6(1): 18 (2024) - Hamza Baniata:
SoK: quantum computing methods for machine learning optimization. Quantum Mach. Intell. 6(2): 47 (2024) - Anna Bernasconi, Alessandro Berti, Gianna M. Del Corso, Riccardo Guidotti, Alessandro Poggiali:
Quantum subroutine for variance estimation: algorithmic design and applications. Quantum Mach. Intell. 6(2): 78 (2024) - Alessandro Berti, Anna Bernasconi, Gianna M. Del Corso, Riccardo Guidotti:
The role of encodings and distance metrics for the quantum nearest neighbor. Quantum Mach. Intell. 6(2): 62 (2024) - Sujit Biswas, Rajat Subhra Goswami, K. Hemant Kumar Reddy:
A cluster-based quantum key distribution with dynamic node selection: an improved approach for scalability and security in quantum communication. Quantum Mach. Intell. 6(2): 63 (2024) - Nicolò Bonaldi, Martina Rossi, Daniele Mattioli, Michele Grapulin, Blanca Silva Fernández, Davide Caputo, Marco Magagnini, Arianna Osti, Fabio Veronese:
Boost clustering with Gaussian Boson Sampling: a quantum-classical hybrid approach. Quantum Mach. Intell. 6(2): 65 (2024) - Nicolò Bonaldi, Martina Rossi, Daniele Mattioli, Michele Grapulin, Blanca Silva Fernández, Davide Caputo, Marco Magagnini, Arianna Osti, Fabio Veronese:
Publisher Correction: Boost clustering with Gaussian Boson Sampling: a quantum-classical hybrid approach. Quantum Mach. Intell. 6(2): 87 (2024) - Paolo Braccia, Pablo Bermejo, Lukasz Cincio, Marco Cerezo:
Computing exact moments of local random quantum circuits via tensor networks. Quantum Mach. Intell. 6(2): 54 (2024) - Shrigyan Brahmachari, Josep Lumbreras, Marco Tomamichel:
Quantum contextual bandits and recommender systems for quantum data. Quantum Mach. Intell. 6(2): 58 (2024) - Giuseppe Buonaiuto, Raffaele Guarasci, Aniello Minutolo, Giuseppe De Pietro, Massimo Esposito:
Quantum transfer learning for acceptability judgements. Quantum Mach. Intell. 6(1): 13 (2024) - Zhiqiang Cai, Jialin Chen, Ke Xu, Lingli Wang:
Recognizing good variational quantum circuits with Monte Carlo Tree Search. Quantum Mach. Intell. 6(2): 36 (2024) - Yen-Jui Chang, Wei-Ting Wang, Hao-Yuan Chen, Shih-Wei Liao, Ching-Ray Chang:
A novel approach for quantum financial simulation and quantum state preparation. Quantum Mach. Intell. 6(1): 24 (2024) - Mahdi Chehimi, Samuel Yen-Chi Chen, Walid Saad, Shinjae Yoo:
Federated quantum long short-term memory (FedQLSTM). Quantum Mach. Intell. 6(2): 43 (2024) - Hao-Yuan Chen, Yen-Jui Chang, Shih-Wei Liao, Ching-Ray Chang:
Deep Q-learning with hybrid quantum neural network on solving maze problems. Quantum Mach. Intell. 6(1): 2 (2024) - Rodrigo Coelho, André Sequeira, Luís Paulo Santos:
VQC-based reinforcement learning with data re-uploading: performance and trainability. Quantum Mach. Intell. 6(2): 53 (2024) - Emmanuel Zambrini Cruzeiro, Christine De Mol, Serge Massar, Stefano Pironio:
Quantum-inspired classification based on quantum state discrimination. Quantum Mach. Intell. 6(2): 79 (2024) - Manuel P. Cuéllar:
What we can do with one qubit in quantum machine learning: ten classical machine learning problems that can be solved with a single qubit. Quantum Mach. Intell. 6(2): 76 (2024) - Sreetama Das, Stefano Martina, Filippo Caruso:
The role of data embedding in equivariant quantum convolutional neural networks. Quantum Mach. Intell. 6(2): 82 (2024) - Alexander Diedrich, Stefan Windmann, Oliver Niggemann:
Solving industrial fault diagnosis problems with quantum computers. Quantum Mach. Intell. 6(2): 66 (2024) - Sebastian Egginger, Alona Sakhnenko, Jeanette Miriam Lorenz:
A hyperparameter study for quantum kernel methods. Quantum Mach. Intell. 6(2): 44 (2024) - Francesca De Falco, Andrea Ceschini, Alessandro Sebastianelli, Bertrand Le Saux, Massimo Panella:
Quantum latent diffusion models. Quantum Mach. Intell. 6(2): 85 (2024) - Jose Falla, Quinn Langfitt, Yuri Alexeev, Ilya Safro:
Graph representation learning for parameter transferability in quantum approximate optimization algorithm. Quantum Mach. Intell. 6(2): 46 (2024) - Kaitlin Gili, Guillermo Alonso, Maria Schuld:
An inductive bias from quantum mechanics: learning order effects with non-commuting measurements. Quantum Mach. Intell. 6(2): 67 (2024) - Fabio A. González, Joseph Alejandro Gallego, Santiago Toledo-Cortés, Vladimir Vargas-Calderón:
Correction: Learning with density matrices and random features. Quantum Mach. Intell. 6(1): 30 (2024) - Vu Tuan Hai, Lawrence H. Le, The Bao Pham:
Exploring the features of quanvolutional neural networks for improved image classification. Quantum Mach. Intell. 6(1): 29 (2024) - Moe Hdaib, Sutharshan Rajasegarar, Lei Pan:
Quantum deep learning-based anomaly detection for enhanced network security. Quantum Mach. Intell. 6(1): 26 (2024) - Jamie Heredge, Charles D. Hill, Lloyd C. L. Hollenberg, Martin Sevior:
Permutation invariant encodings for quantum machine learning with point cloud data. Quantum Mach. Intell. 6(1): 25 (2024)
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