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ORCIDQuantum Machine Intelligence, Volume 5
Volume 5, Number 1, June 2023
- Marina O. Lisnichenko, Stanislav I. Protasov:
Quantum image representation: a review. 1-12 - Sanjaya Lohani
, Sangita Regmi, Joseph M. Lukens, Ryan T. Glasser, Thomas A. Searles, Brian T. Kirby:
Dimension-adaptive machine learning-based quantum state reconstruction. 1-10 - Duarte Magano, Lorenzo Buffoni, Yasser Omar:
Quantum density peak clustering. 1-11 - Massimo Pregnolato, Paola Zizzi:
SARS-CoV-2 spike and ACE2 entanglement-like binding. 1-13 - Haoran Liao, Ian Convy, Zhibo Yang, K. Birgitta Whaley:
Decohering tensor network quantum machine learning models. 1-16 - Péter Mernyei, Konstantinos Meichanetzidis, Ismail Ilkan Ceylan:
Equivariant quantum graph circuits: constructions for universal approximation over graphs. 1-20 - Tianchen Zhao, James Stokes, Shravan K. Veerapaneni:
Meta-variational quantum Monte Carlo. 1-9 - Jure Brence, Dragan Mihailovic, Viktor V. Kabanov, Ljupco Todorovski, Saso Dzeroski, Jaka Vodeb:
Boosting the performance of quantum annealers using machine learning. 1-11 - Haimeng Zhao:
Non-IID quantum federated learning with one-shot communication complexity. 1-11 - E. Ghasemian:
Stationary states of a dissipative two-qubit quantum channel and their applications for quantum machine learning. 1-18 - James Stokes, Saibal De, Shravan K. Veerapaneni, Giuseppe Carleo:
Continuous-variable neural network quantum states and the quantum rotor model. 1-12 - Sascha Mücke, Raoul Heese, Sabine Müller, Moritz Wolter, Nico Piatkowski:
Feature selection on quantum computers. 1-16 - Konstantinos Meichanetzidis, Alexis Toumi, Giovanni de Felice, Bob Coecke:
Grammar-aware sentence classification on quantum computers. 1-16 - Anupama Padha, Anita Sahoo:
MAQML: a Meta-approach to Quantum Machine Learning with Accentuated Sample Variations for Unobtrusive Mental Health Monitoring. 1-17 - Sreetama Das, Jingfu Zhang, Stefano Martina, Dieter Suter, Filippo Caruso:
Quantum pattern recognition on real quantum processing units. 1-17 - Kai Liu, Yuxing Wei, Hai-Sheng Li:
The quantum realization of image linear gray enhancement. 1-14 - Wen-Ran Zhang:
If AI machine cannot think, can QI machine think? - from negative numbers to quantum intelligence for mind-light-matter unity. 1-18 - Francesco Di Marcantonio, Massimiliano Incudini, Davide Tezza, Michele Grossi:
Quantum Advantage Seeker with Kernels (QuASK): a software framework to speed up the research in quantum machine learning. 1-11 - Kai Schärer, Marco Comuzzi:
The quantum threat to blockchain: summary and timeline analysis. 1-12 - André Sequeira, Luís Paulo Santos, Luís Soares Barbosa:
Policy gradients using variational quantum circuits. 1-15 - Tulika Dutta, Siddhartha Bhattacharyya, Bijaya Ketan Panigrahi, Ivan Zelinka, Leo Mrsic:
Multi-level quantum inspired metaheuristics for automatic clustering of hyperspectral images. 1-35 - Supanut Thanasilp, Samson Wang, Nhat A. Nghiem, Patrick J. Coles, Marco Cerezo:
Subtleties in the trainability of quantum machine learning models. 1-22
Volume 5, Number 2, December 2023
- Yan Zhu, Ge Bai, Yuexuan Wang, Tongyang Li, Giulio Chiribella:
Quantum autoencoders for communication-efficient cloud computing. 1-15 - Yuji Cao, Xiyuan Zhou, Xiang Fei, Huan Zhao, Wenxuan Liu, Junhua Zhao:
Linear-layer-enhanced quantum long short-term memory for carbon price forecasting. 1-12 - Stanislav I. Protasov, Marina O. Lisnichenko:
Faster quantum state decomposition with Tucker tensor approximation. 1-10 - Joel E. Pion, Christian F. A. Negre, Susan M. Mniszewski:
Quantum computing for a profusion of postman problem variants. 1-20 - Lirandë Pira, Chris Ferrie:
An invitation to distributed quantum neural networks. 1-24 - Noah L. Wach, Manuel S. Rudolph, Fred Jendrzejewski, Sebastian Schmitt:
Data re-uploading with a single qudit. 1-12 - Davide Cugini, Dario Gerace, Pietro Govoni, Auro Michele Perego, Davide Valsecchi:
Comparing quantum and classical machine learning for Vector Boson Scattering background reduction at the Large Hadron Collider. 1-11 - Cenk Tüysüz, Giuseppe Clemente, Arianna Crippa, Tobias Hartung, Stefan Kühn, Karl Jansen:
Classical splitting of parametrized quantum circuits. 1-19 - Sagnik Chatterjee, Rohan Bhatia, Parmeet Singh Chani, Debajyoti Bera:
Quantum boosting using domain-partitioning hypotheses. 1-20 - Aikaterini Gratsea, Patrick Huembeli:
The effect of the processing and measurement operators on the expressive power of quantum models. 1-12 - Michal Siemaszko, Adam Buraczewski, Bertrand Le Saux, Magdalena Stobinska:
Rapid training of quantum recurrent neural networks. 1-16 - El Amine Cherrat, Iordanis Kerenidis, Anupam Prakash:
Quantum reinforcement learning via policy iteration. 1-18 - Hossein T. Dinani, Diego Tancara, Felipe F. Fanchini, Ariel Norambuena, Raul Coto:
Estimating the degree of non-Markovianity using variational quantum circuits. 1-10 - Roberto Campos, P. A. M. Casares, M. A. Martin-Delgado:
Quantum Metropolis Solver: a quantum walks approach to optimization problems. 1-15 - Michal Koren, Oded Koren, Or Peretz:
A quantum "black box" for entropy calculation. 37 - Salvatore Certo, Anh Pham, Nicolas Robles, Andrew Vlasic:
Conditional generative models for learning stochastic processes. 1-12 - Anthony M. Smaldone, Gregory W. Kyro, Victor S. Batista:
Quantum convolutional neural networks for multi-channel supervised learning. 1-15 - Medina Bandic, Carmen G. Almudéver, Sebastian Feld:
Interaction graph-based characterization of quantum benchmarks for improving quantum circuit mapping techniques. 1-30 - Massimiliano Incudini, Michele Grossi, Andrea Ceschini, Antonio Mandarino, Massimo Panella, Sofia Vallecorsa, David Windridge:
Resource saving via ensemble techniques for quantum neural networks. 1-24 - Asel Sagingalieva, Mohammad Kordzanganeh, Andrii Kurkin, Artem Melnikov, Daniil Kuhmistrov, Michael Perelshtein, Alexey Melnikov, Andrea Skolik, David Von Dollen:
Hybrid quantum ResNet for car classification and its hyperparameter optimization. 1-15 - M. Bilkis, Marco Cerezo, Guillaume Verdon, Patrick J. Coles, Lukasz Cincio:
A semi-agnostic ansatz with variable structure for variational quantum algorithms. 43 - Martins Kalis, Andris Locans, Rolands Sikovs, Hassan Naseri, Andris Ambainis:
A hybrid quantum-classical approach for inference on restricted Boltzmann machines. 44 - Manuel P. Cuéllar, Carlos Cano Gutierrez, Luis G. Baca Ruíz, Lorenzo Servadei:
Time series quantum classifiers with amplitude embedding. 45 - Nozomu Kobayashi, Yoshiyuki Suimon, Koichi Miyamoto, Kosuke Mitarai:
The cross-sectional stock return predictions via quantum neural network and tensor network. 46
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