{"total":31,"rows":[{"id":"2302.09019","title":"Tensor Networks Meet Neural Networks: A Survey and Future Perspectives","created":"2023-01-22","cited_by_count":32,"area":null},{"id":"2106.12974","title":"Tensor networks for unsupervised machine learning","created":"2021-06-24","cited_by_count":21,"area":null},{"id":"2311.11258","title":"Tensor networks for interpretable and efficient quantum-inspired machine learning","created":"2023-11-19","cited_by_count":17,"area":null},{"id":"2202.08177","title":"Generative modeling with projected entangled-pair states","created":"2022-02-16","cited_by_count":16,"area":null},{"id":"2305.19440","title":"Machine learning with tree tensor networks, CP rank constraints, and tensor dropout","created":"2023-05-30","cited_by_count":15,"area":null},{"id":"2106.08334","title":"Quantum-inspired event reconstruction with Tensor Networks: Matrix Product States","created":"2021-06-15","cited_by_count":9,"area":null},{"id":"2202.12319","title":"Privacy-preserving machine learning with tensor networks","created":"2022-02-24","cited_by_count":9,"area":null},{"id":"2203.03366","title":"Improvements to Gradient Descent Methods for Quantum Tensor Network Machine Learning","created":"2022-03-03","cited_by_count":7,"area":null},{"id":"2207.06031","title":"Unsupervised Recognition of Informative Features via Tensor Network Machine Learning and Quantum Entanglement Variations","created":"2022-07-13","cited_by_count":7,"area":null},{"id":"2309.05436","title":"Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models","created":"2023-09-11","cited_by_count":6,"area":null},{"id":"2406.17441","title":"A Matrix Product State Model for Simultaneous Classification and Generation","created":"2024-06-25","cited_by_count":6,"area":null},{"id":"2502.09928","title":"Deep Tree Tensor Networks","created":"2025-02-14","cited_by_count":5,"area":null},{"id":"2201.08878","title":"Classical Simulation of Variational Quantum Classifiers using Tensor Rings","created":"2022-01-21","cited_by_count":3,"area":null},{"id":"2209.15338","title":"Many-body Approximation for Non-negative Tensors","created":"2022-09-30","cited_by_count":3,"area":null},{"id":"2404.11768","title":"Tensor-Networks-based Learning of Probabilistic Cellular Automata Dynamics","created":"2024-04-17","cited_by_count":3,"area":null},{"id":"2512.02547","title":"Tensor Network Based Feature Learning Model","created":"2025-12-02","cited_by_count":3,"area":null},{"id":"2101.02333","title":"Infinitely Wide Tensor Networks as Gaussian Process","created":"2021-01-07","cited_by_count":2,"area":null},{"id":"2107.00195","title":"Non-parametric Semi-Supervised Learning in Many-body Hilbert Space with Rescaled Logarithmic Fidelity","created":"2021-07-01","cited_by_count":2,"area":null},{"id":"2110.03898","title":"Differentiable Programming of Isometric Tensor Networks","created":"2021-10-08","cited_by_count":2,"area":null},{"id":"2209.09098","title":"Deep tensor networks with matrix product operators","created":"2022-09-16","cited_by_count":2,"area":null},{"id":"2305.05318","title":"How Informative is the Approximation Error from Tensor Decomposition for Neural Network Compression?","created":"2023-05-09","cited_by_count":2,"area":null},{"id":"2404.11277","title":"Quantum-inspired Techniques in Tensor Networks for Industrial Contexts","created":"2024-04-17","cited_by_count":2,"area":null},{"id":"2106.11827","title":"Lower and Upper Bounds on the VC-Dimension of Tensor Network Models","created":"2021-06-22","cited_by_count":1,"area":null},{"id":"2405.09005","title":"Cons-training Tensor Networks: Embedding and Optimization Over Discrete Linear Constraints","created":"2024-05-15","cited_by_count":1,"area":null},{"id":"2501.18691","title":"Regularized second-order optimization of tensor-network Born machines","created":"2025-01-30","cited_by_count":1,"area":null},{"id":"2203.16338","title":"Stack operation of tensor networks","created":"2022-03-28","cited_by_count":0,"area":null},{"id":"2307.03884","title":"Noisy Tensor Ring approximation for computing gradients of Variational Quantum Eigensolver for Combinatorial Optimization","created":"2023-07-08","cited_by_count":0,"area":null},{"id":"2404.17645","title":"T\\'ecnicas Quantum-Inspired en Tensor Networks para Contextos Industriales","created":"2024-03-08","cited_by_count":0,"area":null},{"id":"2604.08072","title":"Tensor-Augmented Convolutional Neural Networks: Enhancing Expressivity with Generic Tensor Kernels","created":"2026-04-09","cited_by_count":0,"area":null},{"id":"2604.14287","title":"Quantum-inspired tensor networks in machine learning models","created":"2026-04-15","cited_by_count":0,"area":null},{"id":"2610.06080","title":"Gaussian Universality and Its Breakdown in Tensor-Network Machine Learning","created":"2026-10-05","cited_by_count":0,"area":null}],"next_cursor":null}