State-space models are accurate and efficient neural operators for dynamical systems

28 January 2025

Papers citing "State-space models are accurate and efficient neural operators for dynamical systems"

8 / 8 papers shown

Title
Observability conditions for neural state-space models with eigenvalues and their roots of unity Andrew Gracyk 34 0 0 22 Apr 2025
Sub-Sequential Physics-Informed Learning with State Space Model Chenhui Xu Dancheng Liu Yuting Hu Jiajie Li Ruiyang Qin Qingxiao Zheng Jinjun Xiong AI4CE PINN 68 0 0 01 Feb 2025
Drivetrain simulation using variational autoencoders Pallavi Sharma Jorge-Humberto Urrea-Quintero Bogdan Bogdan Adrian-Dumitru Ciotec Laura Vasilie Henning Wessels Matteo Skull 51 0 0 29 Jan 2025
Automatic selection of the best neural architecture for time series forecasting via multi-objective optimization and Pareto optimality conditions Qianying Cao Shanqing Liu Alan John Varghese Jérome Darbon M. Triantafyllou George Karniadakis AI4TS 79 0 0 21 Jan 2025
Oscillatory State-Space Models T. Konstantin Rusch Daniela Rus AI4TS 42 4 0 04 Oct 2024
Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs Chun-Wun Cheng Jiahao Huang Yi Zhang Guang Yang Carola-Bibiane Schonlieb Angelica I Aviles-Rivero Mamba AI4CE 75 2 0 03 Oct 2024
CMINNs: Compartment Model Informed Neural Networks -- Unlocking Drug Dynamics Nazanin Ahmadi Daryakenari Shupeng Wang George Karniadakis 26 3 0 19 Sep 2024
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 197 2,254 0 18 Oct 2020