Hybrid Quantum-Classical ML

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8 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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Latent-Conditioned Parameterized Quantum Circuits as Universal Approximators for Distributions over Quantum States
May 27, 2026Quoc Hoan Tran, Koki Chinzei, Yasuhiro Endo +1Latent Variable Models Quantum Generative Modeling
Quantum Laboratory, Fujitsu Research, Fujitsu Limited, Kawasaki, Kanagawa 211-8588, Japan
Fermi-Dirac machines as quantizations of neurons
May 23, 2026Alexander He, Nana Liu, Mark M. WildeHybrid Quantum-Classical ML Quantum Neural Networks
Department of Physics, Cornell University, Ithaca, New York 14850, USA · Institute of Natural Sciences, Shanghai Jiao Tong University, Shanghai 200240, China · School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai 200240, China +3
Hybrid Quantum-Classical Corrective Diffusion Modeling for Meteorological Downscaling
May 22, 2026Rui Wang, Edoardo Pasetto, Amer Delilbasic +3Hybrid Quantum-Classical ML Variational Quantum Circuits
Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany · University of Iceland, Reykjav´ık, Iceland · RWTH Aachen University, Aachen, Germany +1
Enhancing Blood Cells Classification using Hybrid Quantum Neural Networks
May 22, 2026Guilherme Cruz, Nouhaila Innan, Alberto Marchisio +2Hybrid Quantum-Classical ML Medical Image Classification
Instituto de Telecomunicac¸˜oes, University of Coimbra, Portugal · 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 +1
Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices
May 21, 2026Farah Elnakhal, Alberto Marchisio, Nouhaila Innan +2Hybrid Quantum-Classical ML Hardware-Aware NAS
Science Division, New York University Abu Dhabi, UAE · 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 +1
A2QTGN: Adaptive Amplitude Quantum-Integrated Temporal Graph Network for Dynamic Link Prediction
May 21, 2026Nouhaila Innan, M. Murali Karthick, Simeon Kandan Sonar +2Temporal GNNs Quantum Machine Learning
1eBRAIN Lab, Division of Engineering, New York University Abu Dhabi (NYUAD), Abu Dhabi, UAE · 3Indian Institute of Technology Palakkad (IITPKD), Palakkad 678623, India · Center for Quantum and Topological Systems (CQTS), NYUAD Research Institute, NYUAD, Abu Dhabi, UAE
Q-SYNTH: Hybrid Quantum-Classical Adversarial Augmentation for Imbalanced Fraud Detection
May 20, 2026Adam Innan, Mansour El Alami, Nouhaila Innan +2Class-Imbalanced Learning Synthetic Data Augmentation
Quantum Physics and Spintronics Team, LPMC, Faculty of Sciences Ben M’sick, Hassan II University of Casablanca, Morocco · eBRAIN Lab, Division of Engineering, New York University Abu Dhabi (NYUAD), Abu Dhabi, UAE · Center for Quantum and Topological Systems (CQTS), NYUAD Research Institute, NYUAD, Abu Dhabi, UAE
Supervised Latent Restructuring for Small-Data Quantum Learning in Plant Phenomics
May 19, 2026Alakananda Mitra, David H. Fleisher, Vangimalla Reddy +1Plant Phenotyping Representation Learning
Nebraska Water Center, IANR University of Nebraska–Lincoln Lincoln, NE 68588 · Adaptive Cropping Systems Laboratory USDA-ARS Beltsville, MD 20705 · Nebraska Water Center, DWFI University of Nebraska–Lincoln Lincoln, NE 68588
Quantum Machine Learning for Cyber-Physical Anomaly Detection in Unmanned Aerial Vehicles: A Leakage-Free Evaluation with Proxy-Audited Feature Sets
May 19, 2026Carlos A. Durán Paredes, Javier E. León Calderón, Nicolás Sánchez Perea +2Cybersecurity Quantum Machine Learning
Corporation for Aerospace Initiatives, Research and Innovation (CASIRI), Popayán, Colombia · Department of Electronics Engineering, Universidad Nacional de Colombia, Manizales, Colombia. · Department of Electronics Engineering, Universidad del Cauca, Popayán, Colombia. +1
Hybrid Quantum-Classical Neural Architecture Search
May 18, 2026Alberto Marchisio, Muhammad Kashif, Nouhaila Innan +1Quantum Machine Learning Hybrid Quantum-Classical ML
eBRAIN Lab, Division of Engineering, New York University Abu Dhabi (NYUAD), Abu Dhabi, United Arab Emirates · Center for Quantum and Topological Systems (CQTS), NYUAD Research Institute, NYUAD, Abu Dhabi, United Arab Emirates
QLIF-CAST: Quantum Leaky-Integrate-and-Fire for Time-Series Weather Forecasting
May 18, 2026Alberto Marchisio, Aayan Ebrahim, Nouhaila Innan +2Multivariate Time Series Forecasting 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
Quantum Sidecar Architectures for Hybrid AI Training and Inference: Stateful Protected Registers, Stateless Reset-and-Reprepare Circuits and Quantum Weight-State Outlook
May 18, 2026Y. Mo, G. D. SuHybrid Quantum-Classical ML
Independent Researcher; BroadLink Co., Ltd. · Associate Professor, Hangzhou Dianzi University
Toward Near-Real-Time Marine Oil Spill Detection in SAR Imagery using Quantum-Assisted SVM
May 17, 2026Joseph Strauss, Jyotsna SharmaRemote Sensing Image Segmentation Quantum Annealing
Division of Computer Science & Engineering Louisiana State University Baton Rouge, United States · Department of Petroleum Engineeering Louisiana State University Baton Rouge, United States
Quantum Feature Pyramid Gating for Seismic Image Segmentation
May 14, 2026Taha Gharaibeh, Jyotsna SharmaImage Segmentation Hybrid Quantum-Classical ML
Louisiana State University Baton Rouge, Louisiana, USA
QuChaTeR: A Hybrid Quantum-Chaotic Temporal Framework for Earthquake Prediction
May 14, 2026Emir Kaan ÖzdemirHybrid Quantum-Classical ML Spatiotemporal Forecasting
Istanbul Erkek High School Ministry of National Education Istanbul, Türkiye · Ministry of National Education
QLAM: A Quantum Long-Attention Memory Approach to Long-Sequence Token Modeling
May 13, 2026Hoang-Quan Nguyen, Sankalp Pandey, Khoa LuuMemory-Augmented Neural Networks Hybrid Quantum-Classical ML
Department of Electrical Engineering and Computer Science, University of Arkansas, AR · Quantum AI Lab, University of Arkansas, AR
Hybrid Quantum-MambaVision: A Quantum-enhanced State Space Model for Calibrated Mixed-type Wafer Defect Detection
May 13, 2026Satwik Sai Prakash Sahoo, Jyoti Prakash Sahoo, Ting Wang +1Multi-Label Classification Hybrid Quantum-Classical ML
Odisha University of Technology and Research, Bhubaneswar, India · National Taiwan University of Science and Technology, Taipei, Taiwan · East China Normal University, Shanghai, China +1
Quantum End-to-End Learning for Contextual Combinatorial Optimization
May 13, 2026Jaehwan Lee, Changhyun KwonCombinatorial Optimization Hybrid Quantum-Classical ML
1KAIST · 2Omelet
Neural Quantum Spectral Operator Learning for Solving Partial Differential Equations
May 12, 2026Chanyoung Kim, Myeonghwan Seong, Yujin Kim +2Hybrid Quantum-Classical ML PDE Operator Learning
KAIST · Department of Statistics and Data Science, Yonsei University · Department of Applied Statistics, Yonsei University +2
Quantum Circuit Simulation of Compartmental Drug Dynamics: Leveraging Variational Algorithms for Nonlinear Mixed-Effects Population Pharmacokinetics
May 10, 2026Isshaan Singh, Nandan PatelHybrid Quantum-Classical ML
School of Computer Science and Engineering Vellore Institute of Technology Chennai, Tamil Nadu 600127, India
Hybrid Quantum-Classical GANs for the Generation of Adversarial Network Flows
May 7, 2026Prateek Paudel, Nitin Jha, Abhishek Parakh +1Adversarial Attacks Network Intrusion Detection
Kennesaw State University, Marietta, GA, USA · University of Nebraska Omaha, Omaha, NE, USA
Medical Imaging Classification with Cold-Atom Reservoir Computing using Auto-Encoders and Surrogate-Driven Training
May 7, 2026Nuno Batista, Ana Morgado, Oscar Ferraz +3Medical Image Analysis Hybrid Quantum-Classical ML
Instituto de Telecomunicac¸˜oes, Dept. of Electrical and Computer Engineering, University of Coimbra, Portugal · CFisUC, Department of Physics, University of Coimbra, Portugal · ISR - Institute of Systems and Robotics, Dept. of Electrical and Computer Engineering, University of Coimbra, Portugal
Quantum-enhanced Large Language Models on Quantum Hardware via Cayley Unitary Adapters
May 7, 2026Borja Aizpurua, Sukhbinder Singh, Augustine Kshetrimayum +2LLM Inference LLM Fine-Tuning
Multiverse Computing, Parque Científico y Tecnológico de Gipuzkoa, Paseo May 7 de Miramón 170, 20014, Donostia / San Sebastián, Spain · Department of Basic Sciences, Tecnun – University of Navarra, San Sebastián, Spain · Multiverse Computing, Centre for Social Innovation, 192 Spadina Avenue, ON M5T 2C2, Toronto, Canada +2
Quantum Kernels for Parity-Structured Classification: A Hybrid Pipeline
May 7, 2026Tushar PandeyQuantum Feature Maps Quantum Machine Learning
Texas A&M University, Department of Mathematics College Station, TX, USA
Generative Quantum-inspired Kolmogorov-Arnold Eigensolver
May 6, 2026Yu-Cheng Lin, Yu-Chao Hsu, I-Shan Tsai +9Quantum Generative Modeling Quantum Chemistry
Department of Electrophysics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan. · National Center for High-Performance Computing, National Institutes of Applied Research, Hsinchu, Taiwan · Cross College Elite Program, National Cheng Kung University, Tainan, Taiwan +7
Quantum Hierarchical Reinforcement Learning via Variational Quantum Circuits
May 5, 2026Yu-Ting Lee, Samuel Yen-Chi Chen, Fu-Chieh ChangHierarchical RL Quantum Machine Learning
Graduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan · Wells Fargo, New York, NY, USA · MediaTek Inc., Hsinchu, Taiwan
Measuring Accuracy and Energy-to-Solution of Quantum Fine-Tuning of Foundational AI Models
May 4, 2026Oliver Knitter, Sang Hyub Kim, Maximilian Wurzer +7Fine-Tuning Energy-Efficient ML
IonQ Inc., 4505 Campus Dr, College Park, MD 20740, USA · QuantumBasel, Schorenweg 44b, 4144 Arlesheim, Switzerland · Center for Quantum Computing and Quantum Coherence (QC2), University of Basel, Klingelbergstrasse 82, 4056 Basel, Switzerland
Entanglement is Half the Story: Post-Selection vs. Partial Traces
May 4, 2026Gustav J L Jäger, Krzysztof Bieniasz, Martin B Plenio +1Tensor Networks Quantum Machine Learning
Institut für KI-Sicherheit, Deutsches Zentrum für Luft- und Raumfahrt e.V., Wilhelm-Runge-Straße 10, Ulm, 89081, Germany. · Institut für Theoretische Physik and IQST, Universität Ulm,2026 Albert-Einstein-Allee 11, Ulm, 89081, Germany.
Hybrid Quantum Reinforcement Learning with QAOA for Improved Vehicle Routing Optimization
May 2, 2026T. Satyanarayana Murthy, B. Swathi Sowmya, Santhosh Voruganti +3Quantum Machine Learning Combinatorial Optimization
Chaitanya Bharathi Institute of Technology Hyderabad, India
Conformalized Quantum DeepONet Ensembles: Towards Scalable Operator Learning with Distribution-Free Guarantees
May 1, 2026Purav Matlia, Christian Moya, Guang LinUncertainty Quantification Hybrid Quantum-Classical ML
Department of Computer Science Purdue University · Department of Mathematics Purdue University · Department of Mathematics Department of Mechanical Engineering Purdue University

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Latent-Conditioned Parameterized Quantum Circuits as Universal Approximators for Distributions over Quantum States

Quoc Hoan Tran, Koki Chinzei, Yasuhiro Endo, Hirotaka Oshima

Quantum Laboratory, Fujitsu Research, Fujitsu Limited, Kawasaki, Kanagawa 211-8588, Japan

Latent Variable Models Quantum Generative Modeling Quantum Machine Learning Hybrid Quantum-Classical ML Barren Plateaus Variational Quantum Circuits+1

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Many applications in quantum simulation, quantum chemistry, and quantum machine learning require not a single quantum state but an ensemble of states characterizing the heterogeneity of a target system. Preparing such ensembles state-by-state is prohibitive in both variational and fault-tolerant settings, thereby motivating a generative modeling approach. We introduce latent-conditioned parameterized quantum circuits (LPQCs), a hybrid quantum-classical framework in which classical neural networks map a latent variable sampled from a prior distribution to the parameters of a parameterized quantum circuit. We prove that LPQCs are universal approximators for probability measures over density operators in the 1-Wasserstein distance, extending classical universal approximation theorems to the quantum-distribution setting. We additionally introduce a multimodal latent prior and a mixture-of-experts circuit architecture, and show empirically that the latent-conditioned parameterization alleviates the barren plateau problem during optimization, a behavior for which we provide rigorous partial guarantees. Numerical experiments validate the framework on a synthetic multi-cluster ensemble of mixed quantum states and on a QM9-derived ensemble of 3-D molecular structures. In these tasks, LPQC outperforms recent quantum generative baselines and matches the generation quality of a classical neural-network baseline, while requiring an output dimension that grows only linearly with the number of qubits rather than exponentially. By leveraging classical expressivity in the latent space, LPQCs offer a tractable route to quantum generative modeling.

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