{"total":18,"rows":[{"id":"2301.10022","title":"Koopman neural operator as a mesh-free solver of non-linear partial differential equations","created":"2023-01-24","cited_by_count":29,"area":null},{"id":"2306.17396","title":"Koopman operator learning using invertible neural networks","created":"2023-06-30","cited_by_count":12,"area":null},{"id":"2301.01104","title":"KoopmanLab: machine learning for solving complex physics equations","created":"2023-01-03","cited_by_count":9,"area":null},{"id":"2506.06454","title":"LETS Forecast: Learning Embedology for Time Series Forecasting","created":"2025-06-06","cited_by_count":6,"area":null},{"id":"2310.06790","title":"Enhancing Predictive Capabilities in Data-Driven Dynamical Modeling with Automatic Differentiation: Koopman and Neural ODE Approaches","created":"2023-10-10","cited_by_count":5,"area":null},{"id":"2211.08992","title":"DLKoopman: A deep learning software package for Koopman theory","created":"2022-11-15","cited_by_count":4,"area":null},{"id":"2112.13982","title":"Quaternion-based dynamic mode decomposition for background modeling in color videos","created":"2021-12-28","cited_by_count":3,"area":null},{"id":"2310.02250","title":"Why should autoencoders work?","created":"2023-10-03","cited_by_count":3,"area":null},{"id":"2503.19717","title":"Invertible Koopman neural operator for data-driven modeling of partial differential equations","created":"2025-03-25","cited_by_count":1,"area":null},{"id":"2510.23215","title":"Accelerating Eigenvalue Dataset Generation via Chebyshev Subspace Filter","created":"2025-10-27","cited_by_count":1,"area":null},{"id":"2512.07542","title":"RRAEDy: Adaptive Latent Linearization of Nonlinear Dynamical Systems","created":"2025-12-08","cited_by_count":1,"area":null},{"id":"2602.14011","title":"KoopGen: Koopman Generator Networks for Representing and Predicting Dynamical Systems with Continuous Spectra","created":"2026-02-15","cited_by_count":1,"area":null},{"id":"2303.06289","title":"Machine Learning Enhanced Hankel Dynamic-Mode Decomposition","created":"2023-03-11","cited_by_count":0,"area":null},{"id":"2502.15093","title":"Forecasting Local Ionospheric Parameters Using Transformers","created":"2025-02-20","cited_by_count":0,"area":null},{"id":"2507.16915","title":"Avoiding spectral pollution for transfer operators using residuals","created":"2025-07-22","cited_by_count":0,"area":null},{"id":"2605.24666","title":"Finding Koopman Invariant Subspaces via Personalized PageRank","created":"2026-05-23","cited_by_count":0,"area":null},{"id":"2606.23957","title":"Learning the Koopman Operator using Attention Free Transformers","created":"2026-06-22","cited_by_count":0,"area":null},{"id":"2608.26943","title":"Data-driven Koopman mode approximation: A neural power iteration algorithm","created":"2026-08-27","cited_by_count":0,"area":null}],"next_cursor":null}