{"total":21,"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":"2210.15435","title":"Grokking phase transitions in learning local rules with gradient descent","created":"2022-10-26","cited_by_count":28,"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":"2307.00908","title":"Quantum Machine Learning on Near-Term Quantum Devices: Current State of Supervised and Unsupervised Techniques for Real-World Applications","created":"2023-07-03","cited_by_count":14,"area":null},{"id":"2206.06597","title":"Permutation Search of Tensor Network Structures via Local Sampling","created":"2022-06-14","cited_by_count":13,"area":null},{"id":"2310.20498","title":"Generative Learning of Continuous Data by Tensor Networks","created":"2023-10-31","cited_by_count":9,"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":"2502.13090","title":"tn4ml: Tensor Network Training and Customization for Machine Learning","created":"2025-02-18","cited_by_count":5,"area":null},{"id":"2208.04372","title":"Generalization and Overfitting in Matrix Product State Machine Learning Architectures","created":"2022-08-08","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":"2209.09098","title":"Deep tensor networks with matrix product operators","created":"2022-09-16","cited_by_count":2,"area":null},{"id":"2603.26604","title":"Hardware-Aware Tensor Networks for Real-Time Quantum-Inspired Anomaly Detection at Particle Colliders","created":"2026-03-27","cited_by_count":2,"area":null},{"id":"2410.09703","title":"Universal scaling laws in quantum-probabilistic machine learning by tensor network towards interpreting representation and generalization powers","created":"2024-10-13","cited_by_count":1,"area":null},{"id":"2412.05674","title":"No-Free-Lunch Theories for Tensor-Network Machine Learning Models","created":"2024-12-07","cited_by_count":1,"area":null},{"id":"2402.17148","title":"Time series generation for option pricing on quantum computers using tensor network","created":"2024-02-27","cited_by_count":0,"area":null},{"id":"2410.06329","title":"Joint Bayesian Parameter and Model Order Estimation for Low-Rank Probability Mass Tensors","created":"2024-10-08","cited_by_count":0,"area":null},{"id":"2603.12026","title":"Efficient Generative Modeling with Unitary Matrix Product States Using Riemannian Optimization","created":"2026-03-12","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":"2605.11471","title":"On the Approximation Complexity of Matrix Product Operator (MPO) Born Machines","created":"2026-05-12","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}