- Frederic Rapp, Marco Roth
:
Quantum Gaussian process regression for Bayesian optimization. Quantum Mach. Intell. 6(1): 5 (2024) - Fabrizio Riguzzi:
Quantum algorithms for weighted constrained sampling and weighted model counting. Quantum Mach. Intell. 6(2): 73 (2024) - Mohit Rohida, Alok Shukla, Prakash Vedula:
Hybrid classical-quantum image processing via polar Walsh basis functions. Quantum Mach. Intell. 6(2): 72 (2024) - Yaniv Romano, Harel Primack, Talya Vaknin, Idan Meirzada, Ilan Karpas, Dov Furman, Chene Tradonsky, Ruti Ben-Shlomi:
Quantum sparse coding. Quantum Mach. Intell. 6(1): 4 (2024) - Abhishek Sadhu, Aritra Sarkar, Akash Kundu:
A quantum information theoretic analysis of reinforcement learning-assisted quantum architecture search. Quantum Mach. Intell. 6(2): 49 (2024) - Lars Simon, Manuel Radons:
On neural quantum support vector machines. Quantum Mach. Intell. 6(1): 3 (2024) - Utkarsh Singh, Aaron Z. Goldberg, Khabat Heshami:
Coherent feed-forward quantum neural network. Quantum Mach. Intell. 6(2): 89 (2024) - Donovan Slabbert, Matt Lourens, Francesco Petruccione:
Pulsar classification: comparing quantum convolutional neural networks and quantum support vector machines. Quantum Mach. Intell. 6(2): 56 (2024) - Apimuk Sornsaeng, Ninnat Dangniam, Thiparat Chotibut:
Quantum next generation reservoir computing: an efficient quantum algorithm for forecasting quantum dynamics. Quantum Mach. Intell. 6(2): 57 (2024) - Teppei Suzuki, Takashi Hasebe, Tsubasa Miyazaki:
Quantum support vector machines for classification and regression on a trapped-ion quantum computer. Quantum Mach. Intell. 6(1): 31 (2024) - Kanimozhi T, Sridevi S, Valliammai M, Mohanraj J, Vinodh Kumar N, Amirthalingam Sathasivam:
Behavior prediction of fiber optic temperature sensor based on hybrid classical quantum regression model. Quantum Mach. Intell. 6(1): 20 (2024) - Hiroyuki Tezuka, Shumpei Uno, Naoki Yamamoto:
Generative model for learning quantum ensemble with optimal transport loss. Quantum Mach. Intell. 6(1): 6 (2024) - Sohum Thakkar, Skander Kazdaghli, Natansh Mathur, Iordanis Kerenidis, André J. Ferreira-Martins, Samurai Brito:
Improved financial forecasting via quantum machine learning. Quantum Mach. Intell. 6(1): 27 (2024) - Sean Tull, Razin A. Shaikh, Sara Sabrina Zemljic, Stephen Clark:
From conceptual spaces to quantum concepts: formalising and learning structured conceptual models. Quantum Mach. Intell. 6(1): 21 (2024) - Ubaid Ullah, Danyal Maheshwari, Cristian Castillo Olea, Begoña García Zapirain:
Sarcopenia risk prediction and feature selection by using quantum machine learning algorithms. Quantum Mach. Intell. 6(2): 80 (2024) - Aswiga R. V, Sridevi S, Indira B:
Leveraging Quantum Kernel Support Vector Machine for breast cancer diagnosis from Digital Breast Tomosynthesis images. Quantum Mach. Intell. 6(2): 40 (2024) - Avi Vadali, Rutuja Kshirsagar, Prasanth Shyamsundar, Gabriel N. Perdue:
Quantum circuit fidelity estimation using machine learning. Quantum Mach. Intell. 6(1): 1 (2024) - Savvas Varsamopoulos, Evan Philip, Vincent E. Elfving, Herman W. T. van Vlijmen, Sairam Menon, Ann Vos, Natalia Dyubankova, Bert Torfs, Anthony Rowe:
Quantum extremal learning. Quantum Mach. Intell. 6(2): 42 (2024) - Sreeraj Rajan Warrier, D. Sri Harshavardhan Reddy, Sriya Bada, Rohith Achampeta, Sebastian Uppapalli, Jayasri Dontabhaktuni:
On-board classification of underwater images using hybrid classical-quantum CNN-based method. Quantum Mach. Intell. 6(2): 70 (2024) - Hadi Wazni, Kin Ian Lo, Lachlan McPheat, Mehrnoosh Sadrzadeh:
Large scale structure-aware pronoun resolution using quantum natural language processing. Quantum Mach. Intell. 6(2): 60 (2024) - David Winderl, Nicola Franco, Jeanette Miriam Lorenz:
Quantum neural networks under depolarization noise: exploring white-box attacks and defenses. Quantum Mach. Intell. 6(2): 83 (2024) - Eric Wulff, Juan Pablo García Amboage, Marcel Aach, Thorsteinn Eli Gislason, Thorsteinn Kristinn Ingolfsson, Tomas Kristinn Ingolfsson, Edoardo Pasetto, Amer Delilbasic, Morris Riedel, Rakesh Sarma, Maria Girone, Andreas Lintermann:
Distributed hybrid quantum-classical performance prediction for hyperparameter optimization. Quantum Mach. Intell. 6(2): 59 (2024) - Jianshe Xie, Cheng Liu, Yumin Dong:
An evolutionary quantum generative adversarial network. Quantum Mach. Intell. 6(2): 84 (2024) - Fei Yan, Abdullah M. Iliyasu, Nianqiao Li, Ahmed S. Salama, Kaoru Hirota:
Quantum robotics: a review of emerging trends. Quantum Mach. Intell. 6(2): 86 (2024) - Enrico Zardini, Enrico Blanzieri, Davide Pastorello:
A quantum k-nearest neighbors algorithm based on the Euclidean distance estimation. Quantum Mach. Intell. 6(1): 23 (2024) - Shiyue Zhang, Aijuan Wang, Lusi Li:
Quantum-convolution-based hybrid neural network model for arrhythmia detection. Quantum Mach. Intell. 6(2): 75 (2024) - 2023
- Medina Bandic, Carmen G. Almudéver, Sebastian Feld:
Interaction graph-based characterization of quantum benchmarks for improving quantum circuit mapping techniques. Quantum Mach. Intell. 5(2): 1-30 (2023) - M. Bilkis, Marco Cerezo, Guillaume Verdon, Patrick J. Coles, Lukasz Cincio:
A semi-agnostic ansatz with variable structure for variational quantum algorithms. Quantum Mach. Intell. 5(2): 43 (2023) - Jure Brence, Dragan Mihailovic, Viktor V. Kabanov, Ljupco Todorovski, Saso Dzeroski, Jaka Vodeb:
Boosting the performance of quantum annealers using machine learning. Quantum Mach. Intell. 5(1): 1-11 (2023) - Roberto Campos, P. A. M. Casares, M. A. Martin-Delgado:
Quantum Metropolis Solver: a quantum walks approach to optimization problems. Quantum Mach. Intell. 5(2): 1-15 (2023)
