DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control

9 September 2020

Papers citing "DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control"

6 / 6 papers shown

Title
True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics Christoph Jürgen Hemmer Daniel Durstewitz AI4TS SyDa AI4CE 22 0 0 19 May 2025
On the Forward Invariance of Neural ODEs Wei Xiao Tsun-Hsuan Wang Ramin Hasani Mathias Lechner Yutong Ban Chuang Gan Daniela Rus 44 11 0 10 Oct 2022
Neural Ordinary Differential Equations for Nonlinear System Identification Aowabin Rahman Ján Drgoňa Aaron Tuor J. Strube 32 22 0 28 Feb 2022
Myriad: a real-world testbed to bridge trajectory optimization and deep learning Nikolaus H. R. Howe Simon Dufort-Labbé Nitarshan Rajkumar Pierre-Luc Bacon 32 5 0 22 Feb 2022
Deconstructing the Inductive Biases of Hamiltonian Neural Networks Nate Gruver Marc Finzi Samuel Stanton A. Wilson AI4CE 28 40 0 10 Feb 2022
Learning Contact Dynamics using Physically Structured Neural Networks Andreas Hochlehnert Alexander Terenin Steindór Sæmundsson M. Deisenroth 19 16 0 22 Feb 2021