On the difficulty of learning chaotic dynamics with RNNs

14 October 2021

Papers citing "On the difficulty of learning chaotic dynamics with RNNs"

8 / 8 papers shown

Title
When are dynamical systems learned from time series data statistically accurate? Jeongjin Park Nicole Yang Nisha Chandramoorthy AI4TS 29 4 0 09 Nov 2024
A scalable generative model for dynamical system reconstruction from neuroimaging data Eric Volkmann Alena Brändle Daniel Durstewitz G. Koppe AI4CE 28 1 0 05 Nov 2024
Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data Manuel Brenner Elias Weber G. Koppe Daniel Durstewitz AI4TS AI4CE 22 2 0 07 Oct 2024
Oscillatory State-Space Models T. Konstantin Rusch Daniela Rus AI4TS 42 4 0 04 Oct 2024
Zero-shot forecasting of chaotic systems Yuanzhao Zhang William Gilpin AI4TS 37 4 0 24 Sep 2024
Predicting Chaotic System Behavior using Machine Learning Techniques Huaiyuan Rao Yichen Zhao Qiang Lai 14 0 0 11 Aug 2024
Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems Manuela Brenner Florian Hess Jonas M. Mikhaeil Leonard Bereska Zahra Monfared Po-Chen Kuo Daniel Durstewitz AI4CE 35 29 0 06 Jul 2022
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