{"total":12,"rows":[{"id":"2406.06210","title":"Quantum Architecture Search: A Survey","created":"2024-06-10","cited_by_count":32,"area":null},{"id":"2407.00736","title":"Quantum Circuit Synthesis and Compilation Optimization: Overview and Prospects","created":"2024-06-30","cited_by_count":8,"area":null},{"id":"2401.11098","title":"Neural auto-designer for enhanced quantum kernels","created":"2024-01-20","cited_by_count":7,"area":null},{"id":"2401.11576","title":"Quantum Architecture Search with Unsupervised Representation Learning","created":"2024-01-21","cited_by_count":4,"area":null},{"id":"2312.01567","title":"Toward Automated Quantum Variational Machine Learning","created":"2023-12-04","cited_by_count":3,"area":null},{"id":"2504.10733","title":"Cross-Problem Parameter Transfer in Quantum Approximate Optimization Algorithm: A Machine Learning Approach","created":"2025-04-14","cited_by_count":3,"area":null},{"id":"2603.14451","title":"How to find expressible and trainable parameterized quantum circuits?","created":"2026-03-15","cited_by_count":2,"area":null},{"id":"2212.11890","title":"Decoding surface codes with deep reinforcement learning and probabilistic policy reuse","created":"2022-12-22","cited_by_count":1,"area":null},{"id":"2310.07858","title":"QArchSearch: A Scalable Quantum Architecture Search Package","created":"2023-10-11","cited_by_count":1,"area":null},{"id":"2411.16560","title":"Quantum Circuit Training with Growth-Based Architectures","created":"2024-11-25","cited_by_count":1,"area":null},{"id":"2509.15451","title":"Neural Architecture Search Algorithms for Quantum Autoencoders","created":"2025-09-18","cited_by_count":1,"area":null},{"id":"2605.27410","title":"Zero-shot Quantum Neural Architecture Search","created":"2026-05-12","cited_by_count":0,"area":null}],"next_cursor":null}