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ORCIDQuantum Machine Intelligence, Volume 4
Volume 4, Number 1, June 2022
- Aikaterini Gratsea
, Patrick Huembeli:
Exploring quantum perceptron and quantum neural network structures with a teacher-student scheme. - Patrick Huembeli, Juan Miguel Arrazola, Nathan Killoran, Masoud Mohseni, Peter Wittek:
The physics of energy-based models. - Vanda Azevedo, Carla Silva, Inês Dutra:
Quantum transfer learning for breast cancer detection. - Prem Kumar Singh:
Bipolar fuzzy attribute implications. - Tak Hur, Leeseok Kim, Daniel K. Park:
Quantum convolutional neural network for classical data classification. - Stefano Martina, Lorenzo Buffoni, Stefano Gherardini, Filippo Caruso:
Learning the noise fingerprint of quantum devices. - Songsong Dai:
Quantum information distance based on classical descriptions. - Ieva Cepaite, Brian Coyle, Elham Kashefi:
A continuous variable Born machine. - Kathleen E. Hamilton, Emily Lynn, Raphael C. Pooser:
Mode connectivity in the loss landscape of parameterized quantum circuits. 1-14 - Yabin Zhang, David J. Gorsich, Paramsothy Jayakumar, Shravan K. Veerapaneni:
Continuous-variable optimization with neural network quantum states. 1-8
Volume 4, Number 2, December 2022
- Stefano Mangini, Alessia Marruzzo, Marco Piantanida, Dario Gerace, Daniele Bajoni, Chiara Macchiavello:
Quantum neural network autoencoder and classifier applied to an industrial case study. 1-13 - Mikel Garcia de Andoin, Javier Echanobe:
Implementable hybrid quantum ant colony optimization algorithm. 1-14 - Nicola Dalla Pozza, Lorenzo Buffoni, Stefano Martina, Filippo Caruso:
Quantum reinforcement learning: the maze problem. 1-10 - Leila Taghavi:
Simplified quantum algorithm for the oracle identification problem. 1-7 - Martina Rossi, Luca Asproni, Davide Caputo, Stefano Rossi, Alice Cusinato, Remo Marini, Andrea Agosti, Marco Magagnini:
Using Shor's algorithm on near term Quantum computers: a reduced version. 1-10 - Ryan LaRose, Eleanor Gilbert Rieffel, Davide Venturelli:
Mixer-phaser Ansätze for quantum optimization with hard constraints. 1-9 - Vladimir Vargas-Calderón, Fabio A. González, Herbert Vinck-Posada:
Optimisation-free density estimation and classification with quantum circuits. 1-9 - Alexander Geng, Ali Moghiseh, Claudia Redenbach, Katja Schladitz:
A hybrid quantum image edge detector for the NISQ era. 1-16 - Niklas Pirnay, Anna Pappa, Jean-Pierre Seifert:
Learning classical readout quantum PUFs based on single-qubit gates. 1-10 - Taisei Nohara, Satoshi Oyama, Itsuki Noda:
Pairwise classification using quantum support vector machine with Kronecker kernel. 1-13 - Bojan Zunkovic:
Deep tensor networks with matrix product operators. 1-12 - Armando Bellante, Alessandro Luongo, Stefano Zanero:
Quantum algorithms for SVD-based data representation and analysis. 1-23 - Alona Sakhnenko, Corey O'Meara, Kumar Jang Bahadur Ghosh, Christian B. Mendl, Giorgio Cortiana, Juan Bernabé-Moreno:
Hybrid classical-quantum autoencoder for anomaly detection. 1-17 - Koji Nagata, Do Ngoc Diep, Tadao Nakamura:
Computational complexity in high-dimensional quantum computing. 1-8 - Behrooz Sepehry, Ehsan Iranmanesh, Michael P. Friedlander, Pooya Ronagh:
Quantum algorithms for structured prediction. 1-25 - Massimiliano Incudini, Fabio Tarocco, Riccardo Mengoni, Alessandra Di Pierro, Antonio Mandarino:
Computing graph edit distance on quantum devices. 1-21 - Fabio A. González, Joseph Alejandro Gallego, Santiago Toledo-Cortés, Vladimir Vargas-Calderón:
Learning with density matrices and random features. 1-17 - Amine Assouel, Antoine Jacquier, Alexei Kondratyev:
A quantum generative adversarial network for distributions. 1-19 - Ryan LaRose, Eleanor Riefel, Davide Venturelli:
Correction to: Mixer‑phaser ansätze for quantum optimization with hard constraints. 1 - Masahiro Kobayashi, Kouhei Nakaji, Naoki Yamamoto:
Overfitting in quantum machine learning and entangling dropout. 1-9
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