Hybrid Quantum-Classical ML

ML: Machine Learning

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Overview

Hybrid quantum-classical machine learning studies how quantum processors can work alongside classical models, often to provide useful feature transformations or compact computational modules. Common approaches include variational quantum circuits as layers or prediction heads in neural networks, quantum kernels, quantum reservoirs, and annealing-based optimization, applied to tasks from image and time-series analysis to physics-informed modeling. The potential value is in representing complex relationships or reducing model size while using classical systems for data handling and computation. Results span small benchmarks and some real-device tests, but whether quantum components offer gains beyond matched classical controls remains an open question, alongside hardware noise, training stability, and execution cost.

Latest papers

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179 papers15 papers in the last four weeks, down 17% on the four weeks before. 0.1% of all new papers.

  1. Photonic Quantum-Enhanced Knowledge Distillation

    Mar 16, 2026Kuan-Cheng Chen, Shang Yu, Chen-Yu Liu +10Knowledge DistillationQuantum Machine Learning

    Department of Electrical and Electronic Engineering, Imperial College London, South Kensington, London, SW7 2AZ, England, United Kingdom. · Imperial Centre for Quantum Engineering, Science and Technology, Imperial College London, South Kensington, London, SW7 2AZ, England, United Kingdom. · JIJ, Rutherford Appleton Laboratory, Harwell Campus, Didcot, OX11 0QX, United Kingdom. +9

  2. Quantum-Enhanced Vision Transformer for Flood Detection using Remote Sensing Imagery

    Mar 14, 2026Soumyajit Maity, Behzad GhanbarianVision TransformerRemote Sensing Image Understanding

    iResearchE3 Lab, Department of Earth and Environmental Sciences, University of Texas at Arlington, Arlington, TX, USA

  3. Embedded Quantum Machine Learning in Embedded Systems: Feasibility, Hybrid Architectures, and Quantum Co-Processors

    Mar 13, 2026Somdip Dey, Syed Muhammad RazaQuantum Machine LearningHybrid Quantum-Classical ML

    School of Engineering and Computing, Regent College London, London, United Kingdom

  4. Quantum entanglement provides a competitive advantage in adversarial games

    Mar 11, 2026Peiyong Wang, Kieran Hymas, James QuachQuantum RLQuantum Machine Learning

    Technology, CSIRO Clayton, Research Way, Clayton, VIC 3168, Australia.

  5. A Hybrid Quantum Circuit Born Machine Framework for Financial Volatility Forecasting: Quantum-Assisted Training and Classical Inference

    Mar 10, 2026Yixiong ChenQuantitative FinanceQuantum Machine Learning

  6. Characterization and upgrade of a quantum graph neural network for charged particle tracking

    Mar 9, 2026Matteo Argenton, Laura Cappelli, Concezio BozziQuantum Neural NetworksHigh-Energy Physics

    Department of Physics and Earth Science, University of Ferrara, Via Saragat 1, Ferrara, 44122, Italy · INFN Ferrara, Via Saragat 1, Ferrara, 44122, Italy

  7. Hybrid Quantum Neural Network for Multivariate Clinical Time Series Forecasting

    Mar 9, 2026Irene Iele, Floriano Caprio, Paolo Soda +1Multivariate Time Series ForecastingTime Series Forecasting

    Unit of Artificial Intelligence and Computer Systems, Università Campus Bio-Medico di Roma, Italy · Department of Diagnostics and Intervention, Radiation Physics, Biomedical Engineering, Umeå University, Sweden · Department of Naval, Electrical, Electronics and Telecommunications Engineering, University of Genoa, Italy

  8. Hybrid Quantum-Classical Encoding for Accurate Residue-Level pKa Prediction

    Mar 9, 2026Van Le, Tan LeMolecular Property PredictionProtein Representation Learning

    the Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA · the School of Engineering, Architecture and Aviation, Hampton University, Hampton, VA 23669, USA

  9. Fermi-Dirac thermal measurements: A framework for quantum hypothesis testing and semidefinite optimization

    Mar 4, 2026Nana Liu, Mark M. WildeQuantum Machine LearningSemidefinite Programming

    Institute of Natural Sciences, School of Mathematical Sciences, Ministry of Education Key Laboratory in Scientific and Engineering Computing, and Global College, Shanghai Jiao Tong University, Shanghai 200240, China · School of Electrical and Computer Engineering, Cornell University, Ithaca, New York 14850, USA

  10. Layer-wise QUBO-Based Training of CNN Classifiers for Quantum Annealing

    Mar 3, 2026Mostafa Atallah, Rebekah HerrmanImage ClassificationHybrid Quantum-Classical ML

    Department of Industrial and Systems Engineering, University of Tennessee - Knoxville, Knoxville, 37996, TN, USA. · Department of Physics, Faculty of Science, Cairo University, Giza, 12613, Egypt.

  11. Neural quantum support vector data description for one-class classification

    Mar 3, 2026Changjae Im, Hyeondo Oh, Daniel K. ParkOne-Class ClassificationHybrid Quantum-Classical ML

    Department of Statistics and Data Science, Yonsei University, Seoul, Republic of Korea · Department of Applied Statistics, Yonsei University, Seoul, Republic of Korea · Department of Quantum Information, Yonsei University, Seoul, Republic of Korea

  12. WTHaar-Net: a Hybrid Quantum-Classical Approach

    Mar 3, 2026Vittorio Palladino, Tsai Idden, Ahmet Enis CetinHybrid Quantum-Classical MLConvolutional Neural Networks

    University of Illinois Chicago (UIC), Chicago, IL, USA · Politecnico di Milano, Department of Electronics, Information and Bioengineering, Milano, Italy

  13. Quantum AS-DeepOnet: Quantum Attentive Stacked DeepONet for Solving 2D Evolution Equations

    Feb 28, 2026Hongquan Wang, Hanshu Chen, Ilia Marchevsky +1PDE Operator LearningDeep Operator Networks

    School of Mathematics, Hohai University, Nanjing, Jiangsu 211100, China · College of Mechanics and Engineering Science, Hohai University, Nanjing, Jiangsu 211100, China · Department of Applied Mathematics, Bauman Moscow State Technical University, Moscow 105005, Russia

  14. Hybrid Quantum Temporal Convolutional Networks

    Feb 27, 2026Junghoon Justin Park, Maria Pak, Sebin Lee +4Quantum Machine LearningHybrid Quantum-Classical ML

    Seoul National University Seoul, Korea · Wells Fargo New York, USA · Brookhaven National Laboratory New York, USA

  15. Quantum Deep Learning: A Comprehensive Review

    Feb 26, 2026Yanjun Ji, Zhao-Yun Chen, Marco Roth +10Quantum Machine LearningQuantum Neural Networks

    Institute for Quantum Computing Analytics (PGI-12), Forschungszentrum Jülich, 52425 Jülich, Germany · Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, Anhui, 230088, P. R. China · Fraunhofer Institute for Manufacturing Engineering and Automation (IPA), Nobelstrasse 12, Stuttgart 70569, Germany +18

  16. Stochastic Neural Networks for Quantum Devices

    Feb 24, 2026Bodo Rosenhahn, Tobias J. Osborne, Christoph HircheQuantum Neural NetworksHybrid Quantum-Classical ML

    Institute for Information Processing (tnt/L3S), Leibniz Universität Hannover, Germany · Institute for Theoretical Physics (ITP/L3S), Leibniz Universität Hannover, Germany

  17. Kaiwu-PyTorch-Plugin: Bridging Deep Learning and Photonic Quantum Computing for Energy-Based Models and Active Sample Selection

    Feb 22, 2026Hongdong Zhu, Qi Gao, Yin Ma +6Hybrid Quantum-Classical MLQuantum Machine Learning

    Beijing QBoson Quantum Technology Co., Ltd. · Chinese Academy of Sciences

  18. Quantum-enhanced satellite image classification

    Feb 20, 2026Qi Zhang, Anton Simen, Carlos Flores-Garrigós +7Hybrid Quantum-Classical MLRemote Sensing Image Understanding

    Kipu Quantum, Greifswalderstrasse 212, 10405 Berlin, Germany · Department of Physical Chemistry, University of the Basque Country UPV/EHU, Apartado 644, 48080 Bilbao, Spain · IDAL, Electronic Engineering Department, ETSE-UV, University of Valencia, Avgda. Universitat s/n, 46100 Burjassot, Valencia, Spain +2

  19. Multi-objective optimization and quantum hybridization of equivariant deep learning interatomic potentials

    Feb 18, 2026G. Laskaris, D. Morozov, D. Tarpanov +6Machine Learning Interatomic PotentialsHybrid Quantum-Classical ML

    Terra Quantum AG, Kornhausstrasse 25, 9000 St. Gallen, Switzerland · LIACS, Leiden University, Netherlands · Nanoscience Center and Department of Chemistry, University of Jyväskylä, P.O. Box 35, 40014 Jyväskylä, Finland +2

  20. Edge-Local and Qubit-Efficient Quantum Graph Learning for the NISQ Era

    Feb 17, 2026Armin Ahmadkhaniha, Jake DoliskaniGraph Representation LearningQuantum Neural Networks

    Department of Computing and Software, McMaster University

  21. Molecular Design beyond Training Data with Novel Extended Objective Functionals of Generative AI Models Driven by Quantum Annealing Computer

    Feb 17, 2026Hayato Kunugi, Mohsen Rahmani, Yosuke Iyama +8Molecular GenerationQuantum Generative Modeling

    Inovation to Implementation Laboratories, Central Pharmaceutical Research Institute, Japan Tobacco Inc., 1-1 Murasaki-cho, Takatsuki, 569-1125, Japan. · D-Wave Systems Inc., 3033 Beta Ave, Burnaby, V5G 4M9, Canada.

  22. Trainability-Oriented Hybrid Quantum Regression via Geometric Preconditioning and Curriculum Optimization

    Jan 17, 2026Qingyu Meng, Yangshuai WangQuantum Machine LearningHybrid Quantum-Classical ML

    Shanghai Jiao Tong University-Chongqing Institute of Artificial Intelligence, Chongqing 401329, China. · Department of Mathematics, National University of Singapore, 10 Lower Kent Ridge Road, Singapore.

  23. Quantum Implicit Neural Representations for Novel View Synthesis

    Jan 8, 2026Daniele Lizzio Bosco, Shuteng Wang, Giuseppe Serra +1Hybrid Quantum-Classical MLNovel View Synthesis

    Department of Mathematics, Computer Science and Physics, University of Udine, Italy · Department of Biology, University of Naples Federico II, Italy · work done during an internship at the 4DQV research group, MPI for Informatics +1

  24. The Role of Quantum in Hybrid Quantum-Classical Neural Networks: An Empirical Assessment

    Jan 8, 2026Dominik Freinberger, Philipp MoserHybrid Quantum-Classical MLQuantum Neural Networks

    Research Unit Medical Informatics, RISC Software GmbH, Softwarepark 32a, Hagenberg, 4232, Upper Austria, Austria.

  25. Quantum-Classical Physics-Informed Neural Networks for Solving Reservoir Seepage Equations

    Dec 3, 2025Xiang Rao, Yina Liu, Yuxuan ShenPDE SolvingPhysics-Informed ML

    School of Petroleum Engineering, Yangtze University, Wuhan 430100, China · College of Future Technology, Yangtze University, Wuhan 430100, China · State Key Laboratory of Low Carbon Catalysis and Carbon Dioxide Utilization (Yangtze University), Wuhan 430100, China +2

  26. Classical and quantum kernel fusion for two-sample testing

    Nov 26, 2025Yu Terada, Yugo Ogio, Ken Arai +2Two-Sample TestingMaximum Mean Discrepancy

    Advanced Research Laboratory, Sony Group Corporation, 1-7-1 Konan, Minato-ku, Tokyo 108-0075, Japan · Deloitte Tohmatsu Consulting LLC.

  27. Quantum Adaptive Self-Attention for Quantum Transformer Models

    Apr 5, 2025Chi-Sheng Chen, En-Jui KuoHybrid Quantum-Classical MLTransformer Attention

    Department of Electrophysics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan

  28. Reducing QPU Calls in Variational Quantum Algorithms via Classical Offloading of Gradient Computation

    Mar 20, 2025Rahul Bhowmick, Harsh Wadhwa, Avinash Singh +3Variational Quantum AlgorithmsQuantum Circuit Trainability

    Quantum Lab, Fujitsu Research of India · Quantum Laboratory, Fujitsu Research, Fujitsu Limited Japan

  29. Classification of Financial Data Using Quantum Support Vector Machine

    Dec 14, 2024Seemanta Bhattacharjee, MD. Muhtasim Fuad, A. K. M. Fakhrul HossainQuantitative FinanceHybrid Quantum-Classical ML

    Shahjalal University Of Science and Technology, Sylhet-3114, Bangladesh