Quantum Machine Learning

Also known as QML

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Overview

Quantum machine learning studies how quantum states, measurements, and computation can support learning from classical or quantum data for tasks such as prediction, generation, sensing, and decision-making. Common approaches include variational quantum circuits and hybrid neural networks, quantum kernels and Gaussian processes, generative models, and learning-theoretic tools such as classical shadows and PAC bounds. Researchers test these methods on image and time-series tasks, molecular prediction, quantum-state and many-body dynamics learning, and reinforcement learning, while addressing data encoding, measurement cost, noise, trainability, and generalization. Evidence remains mixed: particular structured or quantum-data problems may benefit, but broad computational advantage over carefully tuned classical methods is not established and depends on fair, resource-matched evaluation.

Latest papers

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255 papers32 papers in the last four weeks, down 3% on the four weeks before. 0.2% of all new papers.

  1. Unit-Aware Differentially Private Quantum Machine Learning for Clinical and Wearable Health Data

    Oct 20, 2026Md Khalid Syfullah, Alvi Ataur KhalilPrivacy-Preserving MLQuantum Machine Learning

    Computer Science, Southern Illinois University Carbondale, USA

  2. Can Quantum Layers offer Performance and Security Advantages in Vision-Language Models?

    Oct 20, 2026Md Khalid Syfullah, Alvi Ataur KhalilQuantum Machine LearningVLM Robustness

    Computer Science, Southern Illinois University Carbondale, USA

  3. Supervised Learning with Quantum Hamiltonian Embeddings

    Oct 19, 2026Riccardo Molteni, Minjun Jeon, Paolo Braccia +8Quantum Machine LearningQuantum Data Encoding

    IBM Research · Applied Quantum Algorithms ⟨aQaL⟩, Leiden University, The Netherlands · Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PH, United Kingdom +1

  4. Physics-anchored residual quantum neural networks for cloud-cover parameterization

    Oct 19, 2026Zhuo Wang, Ce Yu, Bin YangQuantum Neural NetworksQuantum Machine Learning

    Tianjin University

  5. EmotiQ: A Quantum Residual Specialist Framework for Text Emotion Classification

    Oct 18, 2026Carlton Kigonya, Tanaka Chirara, Yunting YinQuantum NLPEmotion Recognition

    Department of Computer Science, Earlham College, Richmond, IN, USA · Department of Computer Science, Eastern Michigan University, Ypsilanti, MI, USA

  6. Margin-Based Generalization for Quantum Machine Learning with Classical Data Encoding

    Oct 17, 2026Ju-Young Ryu, Tak Hur, Daniel K. ParkQuantum Machine LearningGeneralization Bounds

    Korea Institute of Science and Technology Information, Republic of Korea · Department of Statistics and Data Science, Yonsei University, Republic of Korea · Department of Applied Mathematics, University of Waterloo, Canada +2

  7. Task-aligned spectral inductive biases in parameterized quantum circuits

    Oct 16, 2026Felix Frohnert, Adrián Pérez-Salinas, Sebastian Lange +3Quantum Machine LearningSpectral Bias

    ⟨aQaL⟩Applied Quantum Algorithms, Universiteit Leiden, Leiden, The Netherlands · Dahlem Center for Complex Quantum Systems, Freie Universität Berlin, Germany · Institute for Theoretical Physics, ETH Zürich, Switzerland +2

  8. Same Spectrum, Harder First-Order Training: Phase-Locking in Single- versus Multi-Qubit Re-Uploading Circuits

    Oct 15, 2026Michael Poppel, David Bucher, Maximilian Zorn +5Quantum Circuit TrainabilityQuantum Machine Learning

    Department of Computer Science, LMU Munich, Germany · Aqarios GmbH, Munich, Germany

  9. A Quantum Machine Learning Approach to Content-Based Media Recommendation

    Oct 15, 2026Mina Abbaszadeh, Ouissal Moumou, Anna Pearson +4Quantum NLPRecommender Systems

    Quantinuum United Kingdom · University College London United Kingdom · Relational Intelligence United Kingdom +1

  10. Quantum Versus Classical Machine Learning for Neuropsychiatric Disorders: A Feature-Matched Multi-Cohort Evaluation

    Oct 15, 2026Utsav Poudel, Anuj Nepal, Vyas Viswanath +1Quantum Machine LearningClassification

    School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu 632014, India · Universal Higher Education, Melbourne, Australia

  11. A Tutorial on Quantum Amplitude Embedding with Data Re-Uploading

    Oct 13, 2026Hyojun Ahn, Joongheon KimQuantum Circuit ExpressibilityQuantum Machine Learning

    Department of Electrical & Computer Engineering, Korea University, Seoul, Republic of Korea

  12. Representation Geometry and Inductive Biases in Quantum Classifiers across Classical Visual Benchmarks

    Oct 13, 2026Yu Yamaoka, Weng Ian Chan, Kosuke MitaraiQuantum Machine LearningImage Classification

    Center for Quantum Information and Quantum Biology, The University of Osaka, 1-2 Machikaneyama, Toyonaka, 560-0043, Osaka, Japan. · SANKEN, The University of Osaka, 1-5 Yamadaoka, Suita, 565-0871, Osaka, Japan. · Graduate School of Engineering Science, The University of Osaka, 1-3 Machikaneyama, Toyonaka, 560-8531, Osaka, Japan.

  13. Benchmarking Quantum Kernel SVMs for Credit Card Fraud Detection: Performance Realities Under NISQ Constraints

    Oct 12, 2026Hitanshi Arora, Mohit Swarnkar, Aswani Kumar CherukuriQuantum Machine LearningQuantum Kernel Methods

  14. A 4-Qubit Variational Quantum Classifier for Sequence-Specific Classification of DNMT3A and DNMT3B Flanking Methylation Preferences

    Oct 12, 2026Murat Isik, Yusuf Moinuddin, Humaira Gowher +1Quantum Machine Learning

    Purdue University, West Lafayette, USA · NC State University, Raleigh, USA

  15. VQIL: Visible Quantum Interference Learning for Perturbation Response Ranking on Graphs

    Oct 9, 2026Seokjun Lee, Sergio A. Ortega, Daniel K. Park +1Quantum Machine LearningLearning to Rank

    Milner Therapeutics Institute, University of Cambridge, Cambridge, United Kingdom · Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom · Department of Applied Mathematics and Theoretical Physics, Cambridge Centre for AI in Medicine, University of Cambridge, Cambridge, United Kingdom +9

  16. Trainable Quantum-Native Language Models: Dissipative Memory, Capacity Limits, and Hardware Validation

    Oct 8, 2026Deniz Yunus GöğüşLanguage ModelingQuantum Machine Learning

  17. Large-Scale Benchmarking of Quantum Neural Network Configurations for Financial Time Series Forecasting

    Oct 8, 2026Jack Waller, Xing Liang, Dimitrios Makris +1Quantum Neural NetworksQuantum Machine Learning

    School of Computer Science and Mathematics, Kingston University London, London, KT1 2EE, U.K.. · Department of Electronics and Electrical Engineering, Brunel University of London, London, UB8 3PH, U.K..

  18. Beyond QAOA: A Review of AI and Quantum Computing for Adaptive Combinatorial Optimization

    Oct 8, 2026Hoong Chuin LauCombinatorial OptimizationHybrid Quantum-Classical ML

    School of Computing and Information Systems, Singapore Management University, Singapore

  19. The surprising simplicity of forecasting quantum chaotic many-body dynamics

    Oct 7, 2026Francesco Perciavalle, Agostino Gallo, Francesco Plastina +3Chaotic Time-Series PredictionTime Series Forecasting

    Dipartimento di Fisica, Universit`a della Calabria, Rende 87036, Italy. · INFN, Sezione LNF, gruppo collegato di Cosenza. · Department of Mathematics and Computer Science, University of Calabria, Rende 87036, Italy.

  20. Measurement-Efficient Differentiable Quantum Architecture Search for Combinatorial Optimization

    Oct 7, 2026Lukas Theißinger, Thore Gerlach, Christian BauckhageQuantum Architecture SearchQuantum Machine Learning

    University of Bonn Germany · European Space Agency Netherlands · Lamarr Institute Germany

  21. What a Reporting Convention Hides: A Matched-Budget Audit of Quantum Natural Gradient with an Exactly Computed Metric

    Oct 7, 2026Lu Wei, Yufeng Wang, Haibin LingQuantum Machine LearningVariational Quantum Algorithms

    Stony Brook University · Westlake University

  22. Mu-DisCoCat: A Variational Pipeline for Compositional Generalization on Quantum Processors

    Oct 6, 2026Mina Abbaszadeh, Matilda Karabina Moore, Raem Haq +2Quantum Machine LearningVariational Quantum Circuits

    Department of Computer Science University College London London, United Kingdom · Institute for Logic, Language and Computation University of Amsterdam Amsterdam, Netherlands

  23. Advantage of Entangled Learning Rules in Quantum Measurement Class Learning

    Oct 5, 2026Arka Prabha Das, Abram MagnerQuantum Machine Learning

    Department of Computer Science University at Albany, State University of New York Albany, NY, USA · AI Plus Institute at UAlbany

  24. Learning Disentangled Representations with Quantum Variational Autoencoders

    Oct 5, 2026Gaoyuan Wang, Jerry Tan, Mark GersteinVariational AutoencodersDisentangled Representation Learning

    Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520, USA · Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520, USA · Department of Computer Science, Yale University, New Haven, Connecticut 06520, USA +2

  25. What Does It Cost to Simulate a Quantum Sentence Classifier? An Energy and Compute Perspective on Near-Term QNLP

    Oct 5, 2026Kishlay Kashyap, Sandipan GangulyQuantum NLPQuantum Machine Learning

    Heritage Institute of Technology

  26. Quantum data loading from the learned shared structure of real signals

    Oct 5, 2026Pablo Herrero Gómez, Antonio Jimeno Morenilla, David Muñoz-Hernández +1Quantum Machine LearningQuantum State Preparation

    Department of Computer Science Technology and Computation, Universidad de Alicante, San Vicente del Raspeig, 03690 Alicante, Spain

  27. Variational Quantum Attention for Molecular Graph Learning

    Oct 3, 2026Yu-Cheng Lin, Yu-Chao Hsu, Tai-Yue Li +2Graph Attention NetworksQuantum Machine Learning

    Department of Electrophysics, National Yang Ming Chiao Tung University, Hsinchu 300092, Taiwan. · Department of Internal Medicine, School of Medicine College of Medicine, Taipei Medical University, Taipei, Taiwan · School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea +2

  28. vFedProtoQNAS: Prototype-Guided Personalized Quantum Neural Architecture Search for Virtual Federated Learning

    Oct 1, 2026Seok Bin Son, Samuel Yen-Chi Chen, Soohyun Park +1Quantum Machine LearningQuantum Neural Networks

    Korea University Seoul, Korea · Wells Fargo New York, USA · Sookmyung Women’s University Seoul, Korea

  29. Classical Hardness of Learning Functions of Hamiltonians

    Oct 1, 2026Sota Hashimoto, Akinori KawachiQuantum Machine LearningStatistical Learning Theory

    Graduate School of Engineering, Mie University

  30. Advantage of Sample Complexity in Quantum PAC Learning Requires Inverse Access to State-Preparation Unitaries

    Sep 29, 2026Natsuto Isogai, Satoshi Yoshida, Mio MuraoSample ComplexityQuantum Machine Learning

    Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo, Japan