Quantum Neural Networks

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Quantum neural networks study how quantum states, gates, and measurements can be trained to perform tasks such as classification, forecasting, graph learning, and scientific modeling. Most systems are hybrid: classical networks prepare or process data, while parameterized quantum circuits encode features or serve as trainable model layers; common designs include data re-uploading, quantum convolutional circuits, and quantum attention. Work also explores how encoding, entanglement, circuit architecture, and measurement choices affect expressivity and trainability, with tests ranging from standard image and time-series benchmarks to real quantum hardware. A central tension is whether compact circuits can offer reliable benefits as qubit counts grow, given noise, costly training, and barren plateaus; convincing evidence requires comparisons with strong, parameter-matched classical models.

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135 papers11 papers in the last four weeks, down 15% on the four weeks before. 0.1% of all new papers.

Unit-Aware Differentially Private Quantum Machine Learning for Clinical and Wearable Health Data
Oct 20, 2026Md Khalid Syfullah, Alvi Ataur KhalilPrivacy-Preserving ML Quantum Machine Learning
Computer Science, Southern Illinois University Carbondale, USA
Physics-anchored residual quantum neural networks for cloud-cover parameterization
Oct 19, 2026Zhuo Wang, Ce Yu, Bin YangQuantum Neural Networks Quantum Machine Learning
Tianjin University
EmotiQ: A Quantum Residual Specialist Framework for Text Emotion Classification
Oct 18, 2026Carlton Kigonya, Tanaka Chirara, Yunting YinQuantum NLP Emotion Recognition
Department of Computer Science, Earlham College, Richmond, IN, USA · Department of Computer Science, Eastern Michigan University, Ypsilanti, MI, USA
Large-Scale Benchmarking of Quantum Neural Network Configurations for Financial Time Series Forecasting
Oct 8, 2026Jack Waller, Xing Liang, Dimitrios Makris +1Quantum Neural Networks Quantum 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..
Q-Capsule: A Localized Capsule-Based Quantum Neural Architecture for Barren Plateau Mitigation
Oct 8, 2026Awal Ahmed Fime, Tasfia Zaman Samiha, Saika Zaman +4Quantum Neural Networks Quantum Circuit Trainability
Florida Atlantic University, Boca Raton, Florida, USA · Khulna University of Engineering & Technology, Khulna, Bangladesh · Southern Illinois University Carbondale, Carbondale, Illinois, USA
Q-PhotoMarket: A Design Space Exploration Framework for Photonic Hybrid Quantum Neural Networks in Financial Market Prediction
Oct 7, 2026Alberto Marchisio, Hanzalah Mohamed Siraj, Muhammad Kashif +2Quantum Neural Networks Hybrid Quantum-Classical ML
eBrain Lab, Division of Engineering, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, UAE · Center for Quantum and Topological Systems, NYUAD Research Institute, New York University Abu Dhabi, UAE · SDU Microelectronics, Institute of Mechanical and Electrical Engineering, University of Southern Denmark, Odense, Denmark +1
Quantum Entangled Multimodal Fusion Networks (QEMFN): Resource-Aware Hybrid Vision-Language Fusion via Trainable Entanglement
Oct 6, 2026Srikar Alla, Ali Shiri Sichani, Chi-Ren ShyuMultimodal Fusion Hybrid Quantum-Classical ML
Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA · Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA
When Normalization Selects the Sign: Auditing Robustness Ablations in Quantum Attention
Oct 2, 2026Owen Friedewald, Srikar Alla, Ali Shiri Sichani +1Adversarial Robustness Quantum Neural Networks
Department of Electrical Engineering and Computer Science University of Missouri, Columbia, MO, USA
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 Learning Quantum Neural Networks
Korea University Seoul, Korea · Wells Fargo New York, USA · Sookmyung Women’s University Seoul, Korea
Neural Fourier Surrogates for Data Reuploading Quantum Neural Networks
Sep 30, 2026Oliver Knitter, Jonathan Mei, Sang Hyub Kim +3Neural Surrogate Modeling Frequency-Domain Feature Learning
IonQ Inc., 4505 Campus Drive, College Park, MD 20740, USA.
SQUARE: Structured Quantum Representation Adapters as Compact Quadratic Feature Maps for Frozen Language Models
Sep 29, 2026Emily Jimin Roh, Hyojun Ahn, Hoyeong Lee +4Quantum Feature Maps Representation Learning
Korea University · Sookmyung Women’s University · Ulsan National Institute of Science and Technology +2
Modeling quantum neural network gradient with reinforcement learning
Sep 25, 2026Nhan Trong Luu, Duong Trung Luu, Nam Ngoc Pham +1Quantum Neural Networks Quantum Circuit Trainability
College of Information and Communication Technology, Can Tho University, Can Tho, Vietnam · College of Engineering and Computer Science, VinUniversity, Hanoi, Vietnam · Center for Digital Transformation and Communications, Can Tho University, Can Tho, Vietnam +1
Encryptability As a Coordinate Choice: Depth-One Homomorphic Federated Learning of Quantum Neural Networks
Sep 24, 2026Marcel Mordarski, Nathan Mani, Arshad Patel +2Quantum Federated Learning Privacy-Preserving ML
Department of Computing, Imperial College London London SW7 2AZ, United Kingdom
When Quantum Meets AI: Quantum Methods for Machine Learning and Machine Learning Methods for Quantum Systems
Sep 22, 2026Tak HurNeural Quantum States Quantum Error Correction
Department of Statistics and Data Science Graduate School Yonsei University
Watching Quantum Models Think: Hilbert-Space Interpretability in Quantum Transformer Blocks
Sep 19, 2026Diego Iacopetta, Andrea GaspariniQuantum Neural Networks Transformer Interpretability
Query Machines B.V. Delft, The Netherlands
From IceCube to IT-Sphere: A Hybrid Quantum-Classical GNN for Banking IT Root Cause Analysis
Sep 19, 2026Antonio Greco, Riccardo Paoletti, Roberto Cappuccio +1Root Cause Analysis Hybrid Quantum-Classical ML
Department of Physical Sciences, Earth and Environment (DSFTA), University of Siena, Siena, Italy · Istituto Nazionale di Fisica Nucleare (INFN), Pisa, Italy · IBM Consulting—Promontory, IBM Industry Diamond, Banking & Financial Markets, Milan, Italy
A Hybrid Quantum Neural Network to Analyse Big Experimental Powder X-ray Diffraction Data
Sep 17, 2026H. Dong, S. D. M. Jacques, M. Q. Hlatshwayo +4Quantum Neural Networks Hybrid Quantum-Classical ML
Finden ltd, Building R70, Rutherford Appleton Laboratory, Harwell Science and Innovation Campus, OX11 0QX, UK · National Quantum Computing Centre, Harwell Science and Innovation Campus, OX11 0QX, UK · Department of Chemistry, University College London, 20 Gordon Street, WC1H 0AJ, UK +2
Recursive Quantum Long Short-Term Memory for Stable Short-Horizon Temperature Forecasting
Sep 17, 2026Mu-En Lee, Yen-Ku Liu, Samuel Yen-Chi Chen +1Time Series Forecasting Quantum Machine Learning
University of Toronto, Toronto, ON, Canada · National Yang Ming Chiao Tung University, Hsinchu, Taiwan · Brookhaven National Laboratory, Upton, NY, USA +1
Quantum Graph Convolutional Networks: Implementation and Trainability Analysis
Sep 17, 2026Paul San Sebastian Sein, Theodor Iosif, Tilen G. Limbäck-Stokin +2Graph-Based Semi-Supervised Learning Variational Quantum Circuits
Ikerlan Technology Research Centre, Basque Research and Technology Alliance (BRTA), Arrasate-Mondragon, Spain · University of the Basque Country/Euskal Herriko Unibertsitatea-EHU · Quantum Learning Labs, Department of Computer Science, University College London, London, United Kingdom +4
Learning to Program Adaptive Non-Local Observables for Machine Learning
Sep 16, 2026Yu-Ting Lee, Samuel Yen-Chi Chen, Huan-Hsin TsengVariational Quantum Circuits Quantum Neural Networks
Graduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan · Wells Fargo, New York, NY, USA · Brookhaven National Laboratory, AI & ML Department, Upton, NY, USA
QTrans: A Quantum Transformer for Sentiment Classification
Sep 10, 2026Ren-Xin Zhao, Xinjie Huang, Yahong Liu +4Sentiment Analysis Hybrid Quantum-Classical ML
School of Computer Science, Xiangtan University, Xiangtan 411105, China · School of Electronic Information, Central South University, Changsha 410083, China · Department of Otorhinolaryngology-Head and Neck Surgery, the Third Xiangya Hospital, Central South University, Changsha 410013, China +1
Impact of Data Loss in Postprocessing on Training and Inference of Quantum Neural Networks
Sep 4, 2026Soraya V. Panambalom, Edoardo Altamura, Nick Chancellor +1Quantum Neural Networks
Quantum Group, School of Computing, Newcastle University, 1 Science Square, Newcastle upon Tyne, NE4 5TG, UK · National Quantum Computing Centre, Didcot, OX11 0QX, UK · Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK
A Quantum Variational Approach to Prototypical Recurrent Unit
Sep 3, 2026Mahyar Sadeghi Garjan, Tommaso Cesari, Michel BarbeauQuantum Machine Learning Recurrent Neural Networks
School of Electrical Engineering and Computer Science, University of Ottawa, Canada · School of Computer Science, Carleton University, Ottawa, Canada
A hybrid quantum-classical neural network for learning to route
Aug 31, 2026Marcus Rolf Peter Ritt, Alexsandro Santos da Rosa Júnior, Marcos Vinicius Reballo +2Hybrid Quantum-Classical ML Vehicle Routing
Instituto de Pesquisas Eldorado – Porto Alegre – RS – Brazil · Departamento de Física, Universidade Federal de Santa Catarina, Florianópolis 88040-900, SC, Brazil
Hybrid Variational Quantum-Classical Framework with Adaptive Weighting and Efficiency Assessment
Aug 30, 2026Dilli Hang RaiHybrid Quantum-Classical ML Quantum Neural Networks
Institute of Science and Technology Tribhuvan University, Kritipur, Nepal
Physics-Informed Classical and Quantum Neural Networks for One-Dimensional Schrodinger Eigenvalue Problems
Aug 28, 2026Tariq Mahmood, Waqas Arshad, Bilal Naseer +1Neural PDE Solvers Physics-Informed ML
Centre for High Energy Physics, University of the Punjab, Lahore, Pakistan · Facultad de Ingenier´ıa El´ectrica, Universidad Michoacana de San Nicol´as de Hidalgo, Morelia, Michoac´an, M´exico and Centro de Ciencias Exactas, Universidad del B´ıo-B´ío, Avda. Andr´es Bello 720, Casilla 447, Chill´an, Chile
Comparing Classical and Quantum Machine Learning for Regression in High Energy Physics Collision Data
Aug 28, 2026Tariq Mahmood, Zain ul Abidin, Itzel Luviano Soto +1Quantum Machine Learning Quantum Neural Networks
Centre for High Energy Physics, University of the Punjab, Lahore, Pakistan. · Facultad de Ingenier´ıa Civil, Universidad Michoacana de San Nicol´as de Hidalgo, Morelia, Michoac´an, M´exico · Facultad de Ingenier´ıa El´ectrica, Universidad Michoacana de San Nicol´as de Hidalgo, Morelia, Michoac´an, M´exico +1
Quantum SEDONet: Spectrally-Embedded Quantum Deep Operator Networks for Partial Differential Equations
Aug 27, 2026Muhammad Abid, Arth Sojitra, Bipin Tiwari +1PDE Operator Learning Deep Operator Networks
Department of Mechanical and Aerospace Engineering University of Tennessee, Knoxville Knoxville, TN 37996, USA
QuantumBoostNet: Hybrid Classical-Quantum Cardiac View Identification
Aug 27, 2026Mihai Udrescu-Milosav, Stefan-Alexandru Jura, Mihai Udrescu +1Hybrid Quantum-Classical ML Quantum Neural Networks
Department of Computers and Information Technology Politehnica University TimisÇoara TimisÇoara, Romania · Department of Cardiology & Angiology III Adult Congenital & Valvular Heart Disease Center University Hospital Münster Münster, Germany
Quantum-Inspired Hybrid Neural Networks for Neural Decoding: A Controlled Ablation Study of Learnable Quantum Sidecar Integration
Aug 23, 2026Diana Legziel Levy, Menachem Finkelstein, Peter Chin +2Hybrid Quantum-Classical ML Quantum Neural Networks
Reichman University, Herzliya, Israel · Dartmouth College, USA · The Edmond and Lily Safra Center for Brain Sciences at The Hebrew University of Jerusalem, Israel

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

Md Khalid Syfullah, Alvi Ataur Khalil

Computer Science, Southern Illinois University Carbondale, USA

Privacy-Preserving ML Quantum Machine Learning Differential Privacy Quantum Neural Networks Healthcare Clinical Risk Prediction

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Clinical registries and wearable sensors support early health-risk assessment, yet models trained on these records may leak sensitive information when released. Differential privacy (DP) bounds this leakage by injecting noise whose total magnitude grows with the number of trainable parameters, a cost especially severe for small health cohorts. This motivates parameter efficient models including quantum machine learning (QML), whose variational circuits can represent complex decision boundaries with few trainable parameters. It raises a question: at matched input dimensionality and privacy budget, does a quantum model retain more utility than a classical one? We investigate this question on three clinical cohorts and one wearable cohort, treating each clinical record or participant as a privacy unit. We compare capacity-matched quantum, multilayer perceptron, and logistic regression models across five privacy budgets and five seeds. The quantum model leads on three clinical cohorts by up to 0.104 ROC AUC averaged across budgets; however, trails on the wearable cohort, where the small number of participants requires substantial noise. No difference survives Holm correction across 24 tests, so these results indicate a trend rather than a quantum advantage. An analytic gradient bound shows that lower clipping thresholds can improve utility by reducing noise despite clipping bias. Finally, an experiment on IBM quantum computer (ibm_fez, a 156-qubit superconducting processor) using eight fixed test cases yields mean absolute probability errors of 0.046 (private) and 0.063 (non-private) relative to simulation, supporting the feasibility of inference on noisy intermediate-scale quantum (NISQ) hardware. Code is publicly available at https://github.com/TITANS-Lab-Artifacts/DP-QML-Health.