- Nouhaila Innan
, Owais Ishtiaq Siddiqui, Shivang Arora, Tamojit Ghosh, Yasemin Poyraz Koçak, Dominic Paragas, Abdullah Al Omar Galib, Muhammad Al-Zafar Khan, Mohamed Bennai:
Quantum state tomography using quantum machine learning. Quantum Mach. Intell. 6(1): 28 (2024) - Nouhaila Innan, Abhishek Sawaika, Ashim Dhor, Siddhant Dutta, Sairupa Thota, Husayn Gokal, Nandan Patel, Muhammad Al-Zafar Khan, Ioannis Theodonis, Mohamed Bennai:
Financial fraud detection using quantum graph neural networks. Quantum Mach. Intell. 6(1): 7 (2024) - Yoshiaki Kawase:
Distributed quantum neural networks via partitioned features encoding. Quantum Mach. Intell. 6(1): 15 (2024) - Ali Kookani, Yousef Mafi, Payman Kazemikhah, Hossein Aghababa, Kazim Fouladi, Masoud Barati:
XpookyNet: advancement in quantum system analysis through convolutional neural networks for detection of entanglement. Quantum Mach. Intell. 6(2): 50 (2024) - Michal Koren, Or Peretz:
A quantum procedure for estimating information gain in Boolean classification task. Quantum Mach. Intell. 6(1): 16 (2024) - Chang-Shing Lee, Mei-Hui Wang, Chih-Yu Chen, Sheng-Chi Yang, Marek Z. Reformat, Naoyuki Kubota, Amir Pourabdollah:
Integrating quantum CI and generative AI for Taiwanese/English co-learning. Quantum Mach. Intell. 6(2): 64 (2024) - Yidong Liao, Min-Hsiu Hsieh, Chris Ferrie:
Quantum optimization for training quantum neural networks. Quantum Mach. Intell. 6(1): 33 (2024) - Junyu Liu, Han Zheng, Masanori Hanada, Kanav Setia, Dan Wu:
Quantum power flows: from theory to practice. Quantum Mach. Intell. 6(2): 55 (2024) - Corrado Loglisci, Donato Malerba, Saverio Pascazio:
Quarta: quantum supervised and unsupervised learning for binary classification in domain-incremental learning. Quantum Mach. Intell. 6(2): 68 (2024) - Charles London, Douglas Brown, Wenduan Xu, Sezen Vatansever, Christopher J. Langmead, Dimitri Kartsaklis, Stephen Clark, Konstantinos Meichanetzidis:
Peptide binding classification on quantum computers. Quantum Mach. Intell. 6(1): 35 (2024) - Jishnu Mahmud, Raisa Mashtura, Shaikh Anowarul Fattah, Mohammad Saquib:
Quantum convolutional neural networks with interaction layers for classification of classical data. Quantum Mach. Intell. 6(1): 11 (2024) - Aikaterini Mandilara, Babette Dellen, Uwe Jaekel, Themistoklis Valtinos, Dimitris Syvridis:
Classification of data with a qudit, a geometric approach. Quantum Mach. Intell. 6(1): 17 (2024) - John Mayfield, Issam El-Naqa:
Evaluation of VQC-LSTM for disability forecasting in multiple sclerosis using sequential multisequence MRI. Quantum Mach. Intell. 6(2): 41 (2024) - Shane McFarthing, Anban W. Pillay, Ilya Sinayskiy, Francesco Petruccione:
Classical ensembles of single-qubit quantum variational circuits for classification. Quantum Mach. Intell. 6(2): 81 (2024) - Mauro Mezzini, Fernando Cuartero Gomez, Jose Javier Paulet Gonzalez, Hernan Indibil de la Cruz Calvo, Vicente Pascual, Fernando L. Pelayo:
Polynomial quantum computing algorithms for solving the dualization problem for positive Boolean functions. Quantum Mach. Intell. 6(2): 71 (2024) - Nishikanta Mohanty, Bikash K. Behera, Christopher Ferrie:
Solving the vehicle routing problem via quantum support vector machines. Quantum Mach. Intell. 6(1): 34 (2024) - Angela Rosy Morgillo, Stefano Mangini, Marco Piastra, Chiara Macchiavello:
Quantum state reconstruction in a noisy environment via deep learning. Quantum Mach. Intell. 6(2): 39 (2024) - Yuichiro Mori, Kouhei Nakaji, Yuichiro Matsuzaki, Shiro Kawabata:
Expressive quantum supervised machine learning using Kerr-nonlinear parametric oscillators. Quantum Mach. Intell. 6(1): 14 (2024) - Phuong-Nam Nguyen:
A quantum neural network for sequential data analysis in machine learning. Quantum Mach. Intell. 6(2): 88 (2024) - Xuan-Bac Nguyen, Hoang-Quan Nguyen, Hugh Churchill, Samee U. Khan, Khoa Luu:
Quantum visual feature encoding revisited. Quantum Mach. Intell. 6(2): 61 (2024) - Hiroshi Ohno:
Grover's search with learning oracle for constrained binary optimization problems. Quantum Mach. Intell. 6(1): 12 (2024) - Hiroshi Ohno:
Bayesian network structure learning using quantum generative models. Quantum Mach. Intell. 6(2): 74 (2024) - Hiroshi Ohno:
Adaptive pruning algorithm using a quantum Fisher information matrix for parameterized quantum circuits. Quantum Mach. Intell. 6(2): 77 (2024) - Riccardo Pellini, Maurizio Ferrari Dacrema:
Analyzing the effectiveness of quantum annealing with meta-learning. Quantum Mach. Intell. 6(2): 48 (2024) - Rowan Pellow-Jarman, Anban W. Pillay, Ilya Sinayskiy, Francesco Petruccione:
Hybrid genetic optimization for quantum feature map design. Quantum Mach. Intell. 6(2): 45 (2024) - Or Peretz, Michal Koren:
A parameterized quantum circuit for estimating distribution measures. Quantum Mach. Intell. 6(1): 22 (2024) - Nico Piatkowski, Christa Zoufal:
Quantum circuits for discrete graphical models. Quantum Mach. Intell. 6(2): 37 (2024) - Lirandë Pira, Chris Ferrie:
On the interpretability of quantum neural networks. Quantum Mach. Intell. 6(2): 52 (2024) - Ishaani Priyadarshini:
Swarm-intelligence-based quantum-inspired optimization techniques for enhancing algorithmic efficiency and empirical assessment. Quantum Mach. Intell. 6(2): 69 (2024) - Yang Qian, Yuxuan Du, Dacheng Tao:
Shuffle-QUDIO: accelerate distributed VQE with trainability enhancement and measurement reduction. Quantum Mach. Intell. 6(1): 32 (2024)
