Self-consistent learning of neural dynamical systems from noisy time series

• المؤلفون الرئيسيون: Wang, Zhe, Guet, Claude
• مؤلفون آخرون: School of Physical and Mathematical Sciences
• التنسيق: مقال
• اللغة: English
• منشور في: 2022
• الموضوعات: Engineering::Computer science and engineering; Time Series Analysis; Dynamical Systems
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/162829
• المؤسسة: Nanyang Technological University

We introduce a new method which, for a single noisy time series, provides unsupervised filtering, state space reconstruction, efficient learning of the unknown governing multivariate dynamical system, and deterministic forecasting. We construct both the underlying trajectories and a latent dynamical...