Supervised Learning with Quantum Computers

Stochastic Gradient Descent

Theodoridis, S. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-801522-3.00005-7 · Cited by 44

A simple approach to design quantum neural networks and its applications to kernel-learning methodsPreprint

Shao, C. (2019) · arXiv (Cornell University) · Cited by 2

Optimizing Quantum Variational Circuits with Deep Reinforcement LearningPreprint

Lockwood, O. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2109.03188 · Cited by 12

Quantum Encoding and Analysis on Continuous Time Stochastic Process with Financial ApplicationsPreprint

Zhuang, X., Chen, Z., Xue, C., Wu, Y.-C., & Guo, G. (2022) · RePEc: Research Papers in Economics · doi:10.48550/arxiv.2208.02364 · Cited by 2

Quantum Algorithm for Estimating Largest EigenvaluesPreprint

Vu, N. A. N. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4499001 · Cited by 2

Hybrid Quantum Neural Networks with Amplitude Encoding: Advancing Recovery Rate PredictionsPreprint

Chen, Y., Griffin, P., Recchia, P., Lei, Z., & Zhang, H. (2025) · Qeios · doi:10.32388/vdz7jk · Cited by 2

Model-independent quantum phases classifier

Mahlow, F. R. P., Luiz, F. S., Malvezzi, A. L., & Fanchini, F. F. (2023) · Scientific Reports · doi:10.1038/s41598-023-33301-0 · Cited by 1

Exploring exotic configurations with anomalous features with deep learning: Application of classical and quantum-classical hybrid anomaly detection

Ghosh, K., & Ghosh, S. (2023) · Physical review. B./Physical review. B · doi:10.1103/physrevb.108.165408 · Cited by 1

Variational quantum multidimensional scaling algorithm

Zhang, X., Zhang, F., Guo, Y., & Chen, F. (2024) · Quantum Information Processing · doi:10.1007/s11128-024-04289-x · Cited by 1

Utilizing quantum processor for the analysis of strongly correlated materials

Li, H., Yang, Y., Lv, P., Qu, J., Wang, ‪., Sun, J. P., & Ying, S. (2024) · Physica Scripta · doi:10.1088/1402-4896/ad770b · Cited by 1

Akciğer Röntgen Görüntülerinden Covid-19 ve Zatürre Hastalığının Kuantum Evrişimli Sinir Ağları Yöntemi ile Tahmini

Şahin, S., & Harman, G. (2024) · Karaelmas Science and Engineering Journal · doi:10.7212/karaelmasfen.1416331 · Cited by 1

Performance Evaluation of Quantum and Classical Machine-Learning Models for Breast Cancer Diagnosis

Shah, M. R., Sarraf, J., & Pattnaik, P. K. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-97-0573-3_33 · Cited by 1

Quantum Many-Body Problems: Quantum Machine Learning Applications

Medisetty, P., Vulavalapudi, V. M. S., Evuru, P. C., Mahmud, M., & Prakash, K. B. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-61929-8_12 · Cited by 1

When quantum and classical models disagree: learning beyond minimum norm least square

Thabet, S., Monbroussou, L., Mamon, E. Z., & Landman, J. (2026) · npj Quantum Information · doi:10.1038/s41534-026-01217-y · Cited by 3

A Novel Single-Layer Quantum Neural Network for Approximate SRBB-Based Unitary Synthesis

Belli, G., Mordacci, M., & Amoretti, M. (2026) · Quantum · doi:10.22331/q-2026-03-20-2034 · Cited by 1

Quantum AI-Inspired Blockchain-Assisted Crowdsourced Energy Systems

Mohanapriya, D., Indumathi, R., Subha, K., & Nandhini, K. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-1657-4.ch009 · Cited by 1

On the Quantum Impact in Hybrid Classical-Quantum Transfer Learning

Sünkel, L., Altmann, P. J., Kölle, M., & Gabor, T. (2024) · IEEE International Conference on Quantum Computing and Engineering (QCE) · doi:10.1109/qce60285.2024.10244 · Cited by 1

Quantum computing and artificial intelligence: A synergy for the future

Aleroev, M. A., Arvanova, S. M., & Makienko, D. O. (2025) · ITM Web of Conferences · doi:10.1051/itmconf/20257203007 · Cited by 1

Quantum Image Classification for Sustainable Medical Image Diagnosis

Cruz, M. V., Dhar, S., Hajra, S., Usha, G., & Gautam, K. (2025) · International Conference on Inventive Research in Computing Applications (ICIRCA) · doi:10.1109/icirca65293.2025.11089792 · Cited by 1

Fully Quanvolutional Networks for Time Series Classification

Orka, N. A., Haque, E., Awal, M. A., & Moni, M. A. (2025) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3711896.3736972 · Cited by 1

Quantum AIXI: Universal Intelligence via Quantum Information

Perrier, E. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-00800-8_6 · Cited by 1

Quantum Neural Network Integrating with Gradient Descent Techniques for Enhanced Learning

Vidyullatha, P., Ghantasala, G. S. P., Rajesh Sharma, R., Sungheetha, A., & Ananthanagu, U. (2025) · International Conference on Computing for Sustainable Global Development · doi:10.23919/indiacom66777.2025.11115552 · Cited by 1

Evolution and future directions of video coding standards and emerging compression technologies

Badawy, W. M. (2025) · Multimedia Tools and Applications · doi:10.1007/s11042-025-21108-2 · Cited by 1

Light as a Quantum Agent: Bridging Path Integrals and Reinforcement Learning

Poojary, B. B. (2025) · American Journal of Modern Physics · doi:10.11648/j.ajmp.20251405.11 · Cited by 1

A Hybrid Quantum-Classical Language Model for Text Generation: A Case Study on The Gift of the Magi

Routh, A., & Singh, J. M. (2025) · International Conference on Multidisciplinary Research and Innovations in Engineering (MRIE) · doi:10.1109/mrie66930.2025.11156371 · Cited by 1

The Quantum Advantage in Future Technologies for Supply Chain Optimization

Muralidhar, L. B., Shilpa, R., Kumar, V., Santhosh, Y., & Vainik, V. S. (2025) · IGI Global eBooks · doi:10.4018/979-8-3373-0649-0.ch012 · Cited by 1

Kernel density matrices for probabilistic deep learning

Gonzalez, F. A., Ramos-Pollán, R., & Gallego-Mejia, J. A. (2025) · Quantum Machine Intelligence · doi:10.1007/s42484-025-00299-9 · Cited by 1

Software bug prediction using entanglement-enhanced quantum support vector machines (E-QSVM)

Ayachi, F. E., & Baz, M. E. (2025) · Quantum Machine Intelligence · doi:10.1007/s42484-025-00334-9 · Cited by 1

QTFPred: robust high-performance quantum machine learning modeling that predicts main and cooperative transcription factor bindings with base resolution

Matsubara, T., Machida, S., Owusu, S. P. K., Asakura, A., Hashimoto, H., Matsuoka, M., & Nagasaki, M. (2025) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf604 · Cited by 1

Deep learning for classifying quantum emission signals in WS2 monolayers using wavelet transform

Najaf-Zadeh, H., Raissi, Z., Golmohammady, S., Kaji, P. S., & Esmaeili, M. (2025) · Scientific Reports · doi:10.1038/s41598-025-29120-0 · Cited by 2

Sublinear Classical-to-Quantum Data Encoding Using $n$-Toffoli Gates

Pagni, V., Schmiedinghoff, G., Lively, K., Epping, M., & Felderer, M. (2025) · IEEE International Conference on Quantum Computing and Engineering (QCE) · doi:10.1109/qce65121.2025.00034 · Cited by 1

Hybrid quantum-classical convolutional neural network for astrophysical object classification

Rauf, A., Amin, J., & Nabi, J.-U. (2025) · Physical review. E · doi:10.1103/rnsj-5yjh · Cited by 1

Quantum steganography for secure data transmission

Mogos, G., & Lam, H.-P. (2026) · Cybersecurity · doi:10.1186/s42400-025-00529-4 · Cited by 2

Quantum machine learning with canonical variables

Fuentes, J. (2026) · Quantum Machine Intelligence · doi:10.1007/s42484-026-00373-w · Cited by 1

Quantum neural networks for casting defect detection: a hybrid intelligence framework for smart manufacturing

Yousef, N., Parmar, C., Sata, A. V., & Edacherian, A. (2026) · Quantum Information Processing · doi:10.1007/s11128-026-05113-4 · Cited by 2

Design of a hybrid quantum machine learning architecture and analysis of quantum noise effects

Bravo-Montes, J. A., Martin-Toledano, A., Velasco-Gallego, C., Botella, G., Barrio, A. A. D., & García-Herrero, F. (2026) · Scientific Reports · doi:10.1038/s41598-026-42216-5 · Cited by 1

MRI Brain Tumor Detection using Hybrid Quantum and Classical Neural Networks

Davuluri, R., Jayasree, C., Ahamad, A. N., Lakshmi, C. M., & Sri, A. K. (2026) · International Conference on Image Processing and Capsule Networks (ICIPCN) · doi:10.1109/icipcn67432.2026.11438780 · Cited by 1

Quantum convolutional neural network for slum classification using sentinel-2 imagery

Pai, A. G., Mediboyina, R. K. Y., Buddhiraju, K. M., & Durbha, S. S. (2026) · Quantum Information Processing · doi:10.1007/s11128-026-05134-z · Cited by 1

Cancer in transition: discovery of tumor-intrinsic transcriptional programs shaping the immune and microenvironmental landscape

Spitschak, A., Casalegno‐Garduño, R., & Pützer, B. M. (2026) · Biomarker Research · doi:10.1186/s40364-026-00925-z · Cited by 2

QXRNet: a hybrid CNN–QNN model with resolution-conditioned feature extraction and variational quantum circuit

Vinayak, N., & Ahmad, S. (2026) · Quantum Machine Intelligence · doi:10.1007/s42484-026-00377-6 · Cited by 1

The Variational Quantum Classifier from Qiskit Machine Learning Applied to the Classification of Pulsar Stars

Souza, A. B. M., Cruz, C., Moret, M. A., & Pires, O. M. (2025) · IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) · doi:10.1109/chilecon66915.2025.11476147 · Cited by 1

Entanglement and classical simulability in quantum extreme-learning machines

Lorenzis, A. D., Casado, M. P., Gullo, N. L., Lux, T., Plastina, F., & Riera, A. (2026) · Physical Review Applied · doi:10.1103/891x-ltcy · Cited by 8

EEG-Based Emotion Recognition Using Quantum Kernel–Based Machine Learning

Bhatt, A., Jain, S., Jain, C., Baranwal, A., Sharma, C., & Tiwari, S. (2026) · International Conference on Advancements and Key Challenges in Green Energy and Computing (AKGEC) · doi:10.1109/akgec68790.2026.11485872 · Cited by 1

Quantum algorithm for estimating Olivier-Ricci curvature

Nghiem, N. A., Nguyen, L., Do, K. T., Wei, T.-C., & Phan, T. V. (2026) · Physical Review Research · doi:10.1103/hj52-lksk · Cited by 3

Applied Quantum Machine Learning on PCB Multi-Class Defect Detection

Huang, C.-W., Chen, K.-C., & Lai, C.-J. (2026) · International Conference on Quantum Communications, Networking, and Computing (QCNC) · doi:10.1109/qcnc69040.2026.00174 · Cited by 1

A Quantum Machine Learning Approach for Identifying Energy Theft

Charnaux, A. B., Bouchard, B., & Bouchard, K. (2026) · Procedia Computer Science · doi:10.1016/j.procs.2026.04.106 · Cited by 1

Quantum-Accelerated Artificial Intelligence for Edge Devices: A Review of Encodings, Models, Hybrid Architectures, and NISQ-Era Realities

Singh, R., & Suseelan, A. D. (2026) · Electronics · doi:10.3390/electronics15132832 · Cited by 1

Novel Quantum-Classical Hybrid Circuits for Adaptive Hardware-Based Machine Learning

Sihare, S. R., & Cherukuri, A. K. (2026) · SN Computer Science · doi:10.1007/s42979-026-05194-z · Cited by 1

Shot‐Based Quantum Encoding: A Data‐Loading Paradigm for Quantum Neural Networks

Kyriacou, B., Patapovich, V., Periyasamy, M., & Melnikov, A. A. (2026) · Advanced Computing · doi:10.1002/adco.70004 · Cited by 1

Hybrid Quantum Recurrent Neural Network for Remaining Useful Life Prediction of Turbofan Engines

Tsurkan, O., Konstantinova, A., Senokosov, A., Sagingalieva, A., & Melnikov, A. A. (2026) · Algorithms · doi:10.3390/a19080663 · Cited by 4

Quantum Binary Classification (Student Abstract)

SILVA, C. V. D., Aguiar, A., & Dutra, I. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i18.17941 · Cited by 1

Angewandtes Quantencomputing

Lässig, J. (2020) · Informatik-Spektrum · doi:10.1007/s00287-020-01309-9 · Cited by 1

Supervised Question Classification on SelQA Dataset Using Variational Quantum Classifiers

Katyayan, P., & Joshi, N. (2022) · Lecture notes in networks and systems · doi:10.1007/978-981-19-3679-1_60 · Cited by 1

Constant-time quantum algorithm for homology detection in closed curves

Vu, N. A. N., Gu, X. D., & Wei, T.-C. (2023) · SciPost Physics · doi:10.21468/scipostphys.15.2.049 · Cited by 3

The Impact of Quantum Computing on Artificial Intelligence

Srinivasan, K., & Kesavan, V. (2024) · Advances in computer and electrical engineering book series · doi:10.4018/979-8-3693-1168-4.ch004 · Cited by 1

Quantum K-Nearest Neighbors for Object Recognition

Muntazhar, A. Z. A., Sulistyaningrum, D. R., & Subiono (2024) · Springer proceedings in mathematics & statistics · doi:10.1007/978-981-97-2136-8_11 · Cited by 1

AI-Augmented Decision-Making in Management Using Quantum Networks

Goswami, B., Dixit, M., Asha, V., Mohan, V. C. J., Aswath, S., & Dhanraj, J. A. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-9336-9.ch017 · Cited by 1

Forging Connections Between AI and Quantum Computing in Decentralized Networks

Khachariya, H. D., Isaac, R. A., Sasikala, R., & Gokilavani, M. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-9336-9.ch002 · Cited by 2

Quantum kernels through the lens of entangled tensor kernels

Shin, S., Sweke, R., & Jeong, H. (2026) · Physical Review Research · doi:10.1103/c53t-rybw · Cited by 3

Enhancing Kimberlite Exploration Through Quantum Support Vector Machines: A Comparative Study of Quantum and Classical SVM Approaches

Kumari, M., & Suri, C. (2024) · OITS International Conference on Information Technology (OCIT) · doi:10.1109/ocit65031.2024.00037 · Cited by 1

Exact mean and variance of the squared Hellinger distance for random density matrices

Kumar, V., Vasan, K., & Kumar, S. (2025) · Physical review. E · doi:10.1103/physreve.111.054204 · Cited by 1

Performance comparison of the quantum and classical deep Q-learning approaches in dynamic environments control

Zare, A., & Boroushaki, M. (2025) · EPJ Quantum Technology · doi:10.1140/epjqt/s40507-025-00381-y · Cited by 1

Prediction of Cardiac Disease Using Quantum Enhanced Ensemble Learning Approach

Biju, J. V., Mallya, A. P., & Kirubanantham, P. (2025) · International Conference on Innovative Trends in Information Technology (ICITIIT) · doi:10.1109/icitiit64777.2025.11041018 · Cited by 1

Quantum Computing: Transforming Cybersecurity in the Quantum Era

Saxena, N., & Nigam, A. (2025) · Springer eBooks · doi:10.1007/978-981-96-4948-8_1 · Cited by 2

Hqsan: a hybrid quantum self-attention network for remote sensing image scene classification

Wang, R., Zhang, Z., Shen, Y., Sui, Z., & Lin, K. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-025-07922-3 · Cited by 2

Efficient Quantum Gradient and Higher-Order Derivative Estimation Via Generalized Hadamard Test

Li, D., Dulal, D., Ohorodnikov, M., Wang, H., & Ding, Y. (2025) · IEEE International Conference on Quantum Computing and Engineering (QCE) · doi:10.1109/qce65121.2025.00024 · Cited by 10

Variational Quantum Eigensolver for Clinical Biomarker Discovery: A Multi-Qubit Model

González, J. P. A., Sánchez-Adame, M., & Montiel, O. (2025) · Axioms · doi:10.3390/axioms15010023

Quantum phases classification using quantum machine learning with SHAP-driven feature selection

Franco, G. S., Mahlow, F. R. P., Prado, P. B. B., Pexe, G. E. L., Rattighieri, L. A. M., & Fanchini, F. F. (2026) · Quantum Information Processing · doi:10.1007/s11128-026-05132-1 · Cited by 7

Supervised Quantum State Discrimination

Fanizza, M., Mari, A., & Giovannetti, V. (2019) · Italian Quantum Information Science Conference (IQIS) · doi:10.3390/proceedings2019012021 · Cited by 1

Deep Learning for Gravitational-Wave Data Analysis: A Resampling White-Box Approach

Morales, M. D., Antelis, J. M., Moreno, C., & Nesterov, A. I. (2021) · Sensors · doi:10.3390/s21093174 · Cited by 3

Quantum Classifier with Entangled Subgraph States

Cai, Y., Meng, Y., & Luo, Y. (2021) · International Journal of Theoretical Physics · doi:10.1007/s10773-021-04922-w · Cited by 1

Implementing Quantum-Kernel-Based Classifiers in the NISQ Era

Pillay, S. M., Sinayskiy, I., Jembere, E., & Petruccione, F. (2022) · Communications in computer and information science · doi:10.1007/978-3-030-95070-5_17

Manifestation of quantum images using unitary matrix encoding

Amal, R. S., & Kannan, S. (2022) · The European Physical Journal Plus · doi:10.1140/epjp/s13360-022-02630-w · Cited by 1

Multi-feature Machine Learning with Quantum Superposition

Nguyen, T., Paik, I., & Thang, T. C. (2022) · IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia) · doi:10.1109/icce-asia57006.2022.9954778 · Cited by 1

On quantum ensembles of quantum classifiersPreprint

Abbas, A., Schuld, M., & Petruccione, F. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2001.10833 · Cited by 1

Physicist's Journeys Through the AI World - A Topical Review. There is no royal road to unsupervised learningPreprint

Alhousseini, I., Chemissany, W. A., Kleit, F., & Nasrallah, A. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1905.01023 · Cited by 1

Implications of Quantum Computing for Artificial Intelligence alignment researchPreprint

Sevilla, J., & Moreno, P. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1908.07613 · Cited by 1

Laplacian Eigenmaps with variational circuits: a quantum embedding of graph dataPreprint

Thabet, S., & Hullo, J.-F. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2011.05128 · Cited by 1

Policy Gradients using Variational Quantum CircuitsPreprint

Sequeira, A., Santos, L. P., & Barbosa, L. S. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2203.10591 · Cited by 2

Quantum Approach to Satellite Image Data Compression and AnalysisPreprint

Majji, S. R., Chalumuri, A., & Manoj, B. S. B. S. (2022) · doi:10.36227/techrxiv.21397227 · Cited by 1

Quantum-enhanced Versus Classical Support Vector Machine: An Application to Stock Index ForecastingPreprint

Mercadier, M. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4630419 · Cited by 2

Enhancing Quantum Machine Learning Performance via Transfer Learning TechniquesPreprint

Zeynali, A., & Bakhshi, Z. (2024) · Research Square · doi:10.21203/rs.3.rs-4773157/v1 · Cited by 1

Quantum Computing and Artificial Intelligence: Regulation, Potentialities, Challenges, and the Global LandscapePreprint

Lantyer, V. H. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5218548 · Cited by 2

Quantum Machine Learning: An Application of Quantum Support Vector Machines for Financial Data ClassificationPreprint

Kummara, H. V. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5172167 · Cited by 1

Fuzzy Transform for Analyzing Massive Datasets

Martino, F. D., & Sessa, S. (2020) · Springer eBooks · doi:10.1007/978-3-030-44613-0_12

Production Allocation of Reservoir Layers using Data-Driven Reservoir Modeling

Alessa, S. (2020) · doi:10.33915/etd.7776

Quantum Neural Networks and Quantum Intelligence

Altaĭsky, M. V., & Kaputkina, N. E. (2020) · Studies in Rhythm Engineering · doi:10.1007/978-981-15-7253-1_6

Efficient bit encoding of neural networks for Fock states

Kaestle, O., & Carmele, A. (2021) · Physical Review A · doi:10.1103/physreva.103.062409

K-sparse Pure State Tomography with Phase EstimationPreprint

Gülbahar, B. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.04359

Penyuluhan Machine Learning dan Quantum Artificial Intelligence di Era Industri 4.0

Bunyamin, H., Zakaria, T. M., Widjaja, A., Halim, N., & Sarwoko, V. (2021) · Servirisma · doi:10.21460/servirisma.2021.11.4

Algorithm for operating an ordinary engineering system as a quantum bit

Itami, T., Matsui, N., Isokawa, T., Kouda, N., & Hashimoto, T. (2022) · SICE Journal of Control Measurement and System Integration · doi:10.1080/18824889.2022.2052542

Flight Behavioural Quantification of Mosquitoes using Mask RCNNPreprint

Javed, N., Paradkar, P. N., & Bhatti, A. (2022) · Research Square · doi:10.21203/rs.3.rs-1681007/v1

Eliminate Entanglement in Quantum Information Processing Utilizing Hybrid Quantum-Classical Neural Networks

Isawi, A. S. H. A., & Çevik, M. (2022) · International Congress on Human-Computer Interaction, Optimization and Robotic Applications (ICHORA) · doi:10.1109/hora55278.2022.9799832

COMPARATIVE ANALYSIS OF MACHINE LEARNING ALGORITHMS IN CLASSICAL AND QUANTUM VERSIONS

MENEZES, H. M., & TOMAZELA, M. D. G. J. M. (2022) · CONTECSI - International Conference on Information Systems and Technology Management · doi:10.5748/18contecsi/pos/ssa/6721

A new method of constructing adversarial examples for quantum variational circuits

Yan, J., Yan, L., & Zhang, S. (2022) · Chinese Physics B · doi:10.1088/1674-1056/ac9b32

Quantum Approach to Satellite Image Data Compression and AnalysisPreprint

Majji, S. R., Chalumuri, A., & Manoj, B. S. B. S. (2022) · doi:10.36227/techrxiv.21397227.v1

Introduction to Bayesian Machine Learning

Suyama, A. (2022) · Journal of the Robotics Society of Japan · doi:10.7210/jrsj.40.857

Beyond This Book

Simeone, O. (2022) · Cambridge University Press eBooks · doi:10.1017/9781009072205.021

Epilogue

Simeone, O. (2022) · Cambridge University Press eBooks · doi:10.1017/9781009072205.020

The Pricing of American Options on the Quantum ComputerPreprint

Pracht, R. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4350641

Concise Guide to Quantum Machine Learning

Pastorello, D. (2022) · Machine learning · doi:10.1007/978-981-19-6897-6 · Cited by 17

Quantum Machine Learning: An Applied Approach

Ganguly, S. (2021) · Apress eBooks · doi:10.1007/978-1-4842-7098-1 · Cited by 30

Quantum Machine Learning

Conti, C. (2023) · Quantum science and technology · doi:10.1007/978-3-031-44226-1 · Cited by 10

Quantum computing methods for supervised learning

Kulkarni, V., Kulkarni, M., & Pant, A. (2021) · Quantum Machine Intelligence · doi:10.1007/s42484-021-00050-0 · Cited by 42

Experimental Evaluation Of Quantum Machine Learning

Venkatakrishnasameer, B. (2024) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.12505696