Data-Driven Reduced-Order Modeling of Spatiotemporal Chaos with Neural Ordinary Differential Equations

31 August 2021

Papers citing "Data-Driven Reduced-Order Modeling of Spatiotemporal Chaos with Neural Ordinary Differential Equations"

22 / 22 papers shown

Title
On the relationship between Koopman operator approximations and neural ordinary differential equations for data-driven time-evolution predictions Jake Buzhardt C. Ricardo Constante-Amores Michael D. Graham 68 2 0 20 Nov 2024
When are dynamical systems learned from time series data statistically accurate? Jeongjin Park Nicole Yang Nisha Chandramoorthy AI4TS 36 4 0 09 Nov 2024
Inferring stability properties of chaotic systems on autoencoders' latent spaces Elise Özalp Luca Magri 32 1 0 23 Oct 2024
Modeling chaotic Lorenz ODE System using Scientific Machine Learning Sameera S Kashyap Raj Abhijit Dandekar Rajat Dandekar Sreedath Panat AI4Cl AI4CE 24 0 0 09 Oct 2024
Stability analysis of chaotic systems in latent spaces Elise Özalp Luca Magri 36 3 0 01 Oct 2024
Thinner Latent Spaces: Detecting dimension and imposing invariance through autoencoder gradient constraints George A. Kevrekidis Mauro Maggioni Soledad Villar Y. Kevrekidis DRL 47 0 0 28 Aug 2024
On instabilities in neural network-based physics simulators Daniel Floryan AI4CE 38 2 0 18 Jun 2024
Data-driven low-dimensional model of a sedimenting flexible fiber Andrew J Fox Michael D. Graham AI4CE 22 1 0 16 May 2024
Machine-Learned Closure of URANS for Stably Stratified Turbulence: Connecting Physical Timescales & Data Hyperparameters of Deep Time-Series Models Muralikrishnan Gopalakrishnan Meena Demetri Liousas Andrew D. Simin Aditya Kashi Wesley Brewer James J. Riley S. D. B. Kops AI4TS AI4CE 49 1 0 24 Apr 2024
Building symmetries into data-driven manifold dynamics models for complex flows: application to two-dimensional Kolmogorov flow Carlos E. Pérez De Jesús Alec J. Linot Michael D. Graham AI4CE 35 1 0 15 Dec 2023
Operator Learning for Continuous Spatial-Temporal Model with Gradient-Based and Derivative-Free Optimization Methods Chuanqi Chen Jin-Long Wu AI4CE 34 0 0 20 Nov 2023
Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era E. D. Koronaki N. Evangelou Cristina P. Martin-Linares E. Titi Ioannis G. Kevrekidis 18 6 0 24 Oct 2023
Enhancing Predictive Capabilities in Data-Driven Dynamical Modeling with Automatic Differentiation: Koopman and Neural ODE Approaches Ricardo Constante-Amores Alec J. Linot Michael D. Graham 29 10 0 10 Oct 2023
Unified Long-Term Time-Series Forecasting Benchmark Wenzhuo Zhou Szymon Haponiuk AI4TS 28 2 0 27 Sep 2023
Autoencoders for discovering manifold dimension and coordinates in data from complex dynamical systems Kevin Zeng Carlos E. Pérez De Jesús Andrew J Fox M. Graham AI4CE 51 12 0 01 May 2023
Turbulence control in plane Couette flow using low-dimensional neural ODE-based models and deep reinforcement learning Alec J. Linot Kevin Zeng M. Graham AI4CE 16 19 0 28 Jan 2023
Dynamics of a data-driven low-dimensional model of turbulent minimal Couette flow Alec J. Linot M. Graham AI4CE 16 18 0 11 Jan 2023
Deep learning delay coordinate dynamics for chaotic attractors from partial observable data Charles D. Young M. Graham 11 16 0 20 Nov 2022
Data-driven low-dimensional dynamic model of Kolmogorov flow Carlos E. Pérez De Jesús M. Graham 57 23 0 29 Oct 2022
Data-driven control of spatiotemporal chaos with reduced-order neural ODE-based models and reinforcement learning Kevin Zeng Alec J. Linot M. Graham AI4CE 22 28 0 01 May 2022
Stabilized Neural Ordinary Differential Equations for Long-Time Forecasting of Dynamical Systems Alec J. Linot J. Burby Q. Tang Prasanna Balaprakash M. Graham R. Maulik AI4TS 14 74 0 29 Mar 2022
Data-driven discovery of intrinsic dynamics D. Floryan M. Graham AI4CE 102 72 0 12 Aug 2021