{"total":17,"rows":[{"id":"2111.05458","title":"Which priors matter? Benchmarking models for learning latent dynamics","created":"2021-11-09","cited_by_count":26,"area":null},{"id":"2102.13235","title":"Adaptable Hamiltonian neural networks","created":"2021-02-25","cited_by_count":21,"area":null},{"id":"2502.02480","title":"Stable Port-Hamiltonian Neural Networks","created":"2025-02-04","cited_by_count":13,"area":null},{"id":"2106.00026","title":"Machine-Learning Non-Conservative Dynamics for New-Physics Detection","created":"2021-05-31","cited_by_count":10,"area":null},{"id":"2308.01084","title":"Data-Driven Identification of Quadratic Representations for Nonlinear Hamiltonian Systems using Weakly Symplectic Liftings","created":"2023-08-02","cited_by_count":6,"area":null},{"id":"2501.12116","title":"Efficient PINNs via Multi-Head Unimodular Regularization of the Solutions Space","created":"2025-01-21","cited_by_count":6,"area":null},{"id":"2111.05986","title":"SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision","created":"2021-11-10","cited_by_count":5,"area":null},{"id":"2204.05077","title":"Learning Trajectories of Hamiltonian Systems with Neural Networks","created":"2022-04-11","cited_by_count":4,"area":null},{"id":"2104.14474","title":"Learning Hamiltonian dynamics by reservoir computer","created":"2021-04-24","cited_by_count":2,"area":null},{"id":"2303.13562","title":"Learning unidirectional coupling using echo-state network","created":"2023-03-23","cited_by_count":2,"area":null},{"id":"2509.13425","title":"Unified Spatiotemporal Physics-Informed Learning (USPIL): A Framework for Modeling Complex Predator-Prey Dynamics","created":"2025-09-16","cited_by_count":1,"area":null},{"id":"2604.17470","title":"Machine Learning Hamiltonian Dynamical Systems with Sparse and Noisy Data","created":"2026-04-19","cited_by_count":1,"area":null},{"id":"2204.04348","title":"Neuronal diversity can improve machine learning for physics and beyond","created":"2022-04-09","cited_by_count":0,"area":null},{"id":"2212.06929","title":"Generating extreme quantum scattering in graphene with machine learning","created":"2022-12-13","cited_by_count":0,"area":null},{"id":"2403.08194","title":"Unsupervised Learning of Hybrid Latent Dynamics: A Learn-to-Identify Framework","created":"2024-03-13","cited_by_count":0,"area":null},{"id":"2606.28158","title":"Recovering Sharp Conductivity Features in the Finite-Data Calder\\'on Problem with Physics-Informed Neural Networks","created":"2026-06-26","cited_by_count":0,"area":null},{"id":"2606.30117","title":"Gravitational Duals from Equations of State II: Large Hierarchies and False Vacua","created":"2026-06-29","cited_by_count":0,"area":null}],"next_cursor":null}