Cover Image

Universality of Many-body Projected Ensemble for Learning Quantum Data Distribution

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tran, Quoc Hoan, Chinzei, Koki, Endo, Yasuhiro, Oshima, Hirotaka
Format:	Preprint
Published:	2026
Subjects:	Quantum Physics Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Latent-Conditioned Parameterized Quantum Circuits as Universal Approximators for Distributions over Quantum States
by: Tran, Quoc Hoan, et al.
Published: (2026)

Learning Quantum Data Distribution via Chaotic Quantum Diffusion Model
by: Tran, Quoc Hoan, et al.
Published: (2026)

Resource-efficient equivariant quantum convolutional neural networks
by: Chinzei, Koki, et al.
Published: (2024)

Learning quantum many-body data locally: A provably scalable framework
by: Chinzei, Koki, et al.
Published: (2025)

Trade-off between Gradient Measurement Efficiency and Expressivity in Deep Quantum Neural Networks
by: Chinzei, Koki, et al.
Published: (2024)

Iterative Quantum Feature Maps
by: Matsumoto, Nasa, et al.
Published: (2025)

Quantum Curriculum Learning
by: Tran, Quoc Hoan, et al.
Published: (2024)

Splitting and Parallelizing of Quantum Convolutional Neural Networks for Learning Translationally Symmetric Data
by: Chinzei, Koki, et al.
Published: (2023)

Molecular Quantum Transformer
by: Kamata, Yuichi, et al.
Published: (2025)

Iterative Quantum Feature Maps
by: Nasa Matsumoto, et al.
Published: (2026)

Extending echo state property for quantum reservoir computing
by: Kobayashi, Shumpei, et al.
Published: (2024)

Coherence influx is indispensable for quantum reservoir computing
by: Kobayashi, Shumpei, et al.
Published: (2024)

Enhancing variational quantum algorithms by balancing training on classical and quantum hardware
by: Bhowmick, Rahul, et al.
Published: (2025)

Exponential Improvement on Asian Option Pricing Through Quantum Preconditioning Methods
by: Rendon, Gumaro, et al.
Published: (2025)

Scalable Quantum-Inspired Optimization through Dynamic Qubit Compression
by: Tran, Co, et al.
Published: (2024)

Quantum Ensemble for Classification
by: Macaluso, Antonio, et al.
Published: (2020)

Learning Minimal Representations of Many-Body Physics from Snapshots of a Quantum Simulator
by: Møller, Frederik, et al.
Published: (2025)

Quantum Attention by Overlap Interference: Predicting Sequences from Classical and Many-Body Quantum Data
by: Pecilli, Alessio, et al.
Published: (2026)

Characterizing Many-body Dynamics with Projected Ensembles on a Superconducting Quantum Processor
by: Yan, Zhiguang, et al.
Published: (2025)

Quantum Generative Diffusion Model: A Fully Quantum-Mechanical Model for Generating Quantum State Ensemble
by: Chen, Chuangtao, et al.
Published: (2024)

Exponential Quantum Communication Advantage in Distributed Inference and Learning
by: Gilboa, Dar, et al.
Published: (2023)

Distributed and Secure Kernel-Based Quantum Machine Learning
by: Swaminathan, Arjhun, et al.
Published: (2024)

Quantum Privacy Aggregation of Teacher Ensembles (QPATE) for Privacy-preserving Quantum Machine Learning
by: Watkins, William, et al.
Published: (2024)

Function Smoothing Regularization for Precision Factorization Machine Annealing in Continuous Variable Optimization Problems
by: Endo, Katsuhiro, et al.
Published: (2024)

Generative Quantum Data Embeddings for Supervised Learning
by: Heo, Jaewoong, et al.
Published: (2026)

Parametric Quantum State Tomography with HyperRBMs
by: Tonner, Simon, et al.
Published: (2026)

Machine Failure Detection Based on Projected Quantum Models
by: Bowden, Larry, et al.
Published: (2026)

Quantum Algorithms for Projection-Free Sparse Convex Optimization
by: He, Jianhao, et al.
Published: (2025)

Blockchain Network Analysis using Quantum Inspired Graph Neural Networks & Ensemble Models
by: D'Amico, Luigi, et al.
Published: (2025)

Solving The Quantum Many-Body Hamiltonian Learning Problem with Neural Differential Equations
by: Heightman, Timothy, et al.
Published: (2024)

Detection of Physiological Data Tampering Attacks with Quantum Machine Learning
by: Onim, Md. Saif Hassan, et al.
Published: (2025)

Experimental Machine Learning with Classical and Quantum Data via NMR Quantum Kernels
by: Sabarad, Vivek, et al.
Published: (2024)

Universal Matrix Multiplication on Quantum Computer
by: Yao, Jiaqi, et al.
Published: (2024)

Quantum Transfer Learning Shows Improved Robustness in Low-Data Regimes
by: Lo, Li-An, et al.
Published: (2026)

Overcoming Dimensional Factorization Limits in Discrete Diffusion Models through Quantum Joint Distribution Learning
by: Chen, Chuangtao, et al.
Published: (2025)

Adversarial Robustness in Distributed Quantum Machine Learning
by: Kananian, Pouya, et al.
Published: (2025)

Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
by: Gao, Nicholas, et al.
Published: (2024)

Distribution-Guided and Constrained Quantum Machine Unlearning
by: Malik, Nausherwan, et al.
Published: (2026)

Quantum Geometry of Data
by: Abanov, Alexander G., et al.
Published: (2025)

BCQQ: Batch-Constraint Quantum Q-Learning with Cyclic Data Re-uploading
by: Periyasamy, Maniraman, et al.
Published: (2023)