no code implementations • 31 Mar 2023 • Aiqing Zhu, Tom Bertalan, Beibei Zhu, Yifa Tang, Ioannis G. Kevrekidis
We thus formulate an adaptive algorithm which monitors the level of error and adapts the number of (unrolled) implicit solution iterations during the training process, so that the error of the unrolled approximation is less than the current learning loss.
1 code implementation • 15 Jun 2022 • Aiqing Zhu, Pengzhan Jin, Beibei Zhu, Yifa Tang
The combination of ordinary differential equations and neural networks, i. e., neural ordinary differential equations (Neural ODE), has been widely studied from various angles.
1 code implementation • 29 Apr 2022 • Aiqing Zhu, Beibei Zhu, Jiawei Zhang, Yifa Tang, Jian Liu
We propose volume-preserving networks (VPNets) for learning unknown source-free dynamical systems using trajectory data.