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Stabilized Neural Ordinary Differential Equations for Long-Time
  Forecasting of Dynamical Systems

Stabilized Neural Ordinary Differential Equations for Long-Time Forecasting of Dynamical Systems

29 March 2022
Alec J. Linot
J. Burby
Q. Tang
Prasanna Balaprakash
M. Graham
R. Maulik
    AI4TS
ArXivPDFHTML

Papers citing "Stabilized Neural Ordinary Differential Equations for Long-Time Forecasting of Dynamical Systems"

30 / 30 papers shown
Title
Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaos
Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaos
Chris Pedersen
L. Zanna
Joan Bruna
50
1
0
24 Mar 2025
Deep Learning for Time Series Forecasting: A Survey
X. Kong
Zhenghao Chen
Weiyao Liu
Kaili Ning
Lechao Zhang
Syauqie Muhammad Marier
Yichen Liu
Yuhao Chen
Feng Xia
AI4TS
AI4CE
53
4
0
13 Mar 2025
Exploring Neural Ordinary Differential Equations as Interpretable Healthcare classifiers
Shi Li
AI4CE
65
0
0
05 Mar 2025
Deep Learning of the Evolution Operator Enables Forecasting of Out-of-Training Dynamics in Chaotic Systems
Deep Learning of the Evolution Operator Enables Forecasting of Out-of-Training Dynamics in Chaotic Systems
Ira J. S. Shokar
Peter H. Haynes
R. Kerswell
AI4TS
40
1
0
28 Feb 2025
Invariant Measures for Data-Driven Dynamical System Identification: Analysis and Application
Jonah Botvinick-Greenhouse
56
0
0
31 Jan 2025
Training Stiff Neural Ordinary Differential Equations with Explicit
  Exponential Integration Methods
Training Stiff Neural Ordinary Differential Equations with Explicit Exponential Integration Methods
Colby Fronk
Linda R. Petzold
71
2
0
02 Dec 2024
Mitigating Time Discretization Challenges with WeatherODE: A Sandwich
  Physics-Driven Neural ODE for Weather Forecasting
Mitigating Time Discretization Challenges with WeatherODE: A Sandwich Physics-Driven Neural ODE for Weather Forecasting
Peiyuan Liu
Tian Zhou
Liang Sun
Rong Jin
AI4CE
32
0
0
09 Oct 2024
Training Stiff Neural Ordinary Differential Equations with Implicit
  Single-Step Methods
Training Stiff Neural Ordinary Differential Equations with Implicit Single-Step Methods
Colby Fronk
Linda R. Petzold
34
4
0
08 Oct 2024
Improved deep learning of chaotic dynamical systems with multistep
  penalty losses
Improved deep learning of chaotic dynamical systems with multistep penalty losses
Dibyajyoti Chakraborty
Seung Whan Chung
Ashesh Chattopadhyay
R. Maulik
AI4CE
24
1
0
08 Oct 2024
Stability analysis of chaotic systems in latent spaces
Stability analysis of chaotic systems in latent spaces
Elise Özalp
Luca Magri
36
3
0
01 Oct 2024
On latent dynamics learning in nonlinear reduced order modeling
On latent dynamics learning in nonlinear reduced order modeling
N. Farenga
S. Fresca
Simone Brivio
Andrea Manzoni
AI4CE
36
1
0
27 Aug 2024
On instabilities in neural network-based physics simulators
On instabilities in neural network-based physics simulators
Daniel Floryan
AI4CE
40
2
0
18 Jun 2024
Data-driven low-dimensional model of a sedimenting flexible fiber
Data-driven low-dimensional model of a sedimenting flexible fiber
Andrew J Fox
Michael D. Graham
AI4CE
24
1
0
16 May 2024
Machine-Learned Closure of URANS for Stably Stratified Turbulence:
  Connecting Physical Timescales & Data Hyperparameters of Deep Time-Series
  Models
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
Systematic construction of continuous-time neural networks for linear
  dynamical systems
Systematic construction of continuous-time neural networks for linear dynamical systems
Chinmay Datar
Adwait Datar
Felix Dietrich
W. Schilders
AI4TS
44
1
0
24 Mar 2024
Out-of-Domain Generalization in Dynamical Systems Reconstruction
Out-of-Domain Generalization in Dynamical Systems Reconstruction
Niclas Alexander Göring
Florian Hess
Manuel Brenner
Zahra Monfared
Daniel Durstewitz
AI4CE
38
10
0
28 Feb 2024
Generative Learning for Forecasting the Dynamics of Complex Systems
Generative Learning for Forecasting the Dynamics of Complex Systems
Han Gao
Sebastian Kaltenbach
Petros Koumoutsakos
AI4TS
AI4CE
40
6
0
27 Feb 2024
Enhancing Dynamical System Modeling through Interpretable Machine
  Learning Augmentations: A Case Study in Cathodic Electrophoretic Deposition
Enhancing Dynamical System Modeling through Interpretable Machine Learning Augmentations: A Case Study in Cathodic Electrophoretic Deposition
Christian L. Jacobsen
Jiayuan Dong
Mehdi Khalloufi
Xun Huan
Karthik Duraisamy
Maryam Akram
Wanjiao Liu
25
1
0
16 Jan 2024
AI-Lorenz: A physics-data-driven framework for black-box and gray-box
  identification of chaotic systems with symbolic regression
AI-Lorenz: A physics-data-driven framework for black-box and gray-box identification of chaotic systems with symbolic regression
Mario De Florio
Ioannis G. Kevrekidis
George Karniadakis
49
16
0
21 Dec 2023
Building symmetries into data-driven manifold dynamics models for complex flows: application to two-dimensional Kolmogorov flow
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
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
Enhancing Predictive Capabilities in Data-Driven Dynamical Modeling with
  Automatic Differentiation: Koopman and Neural ODE Approaches
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
32
10
0
10 Oct 2023
Interpretable learning of effective dynamics for multiscale systems
Interpretable learning of effective dynamics for multiscale systems
Emmanuel Menier
Sebastian Kaltenbach
Mouadh Yagoubi
Marc Schoenauer
Petros Koumoutsakos
AI4CE
36
6
0
11 Sep 2023
A Multifidelity deep operator network approach to closure for multiscale
  systems
A Multifidelity deep operator network approach to closure for multiscale systems
Shady E. Ahmed
P. Stinis
AI4CE
33
13
0
15 Mar 2023
Quantifying uncertainty for deep learning based forecasting and
  flow-reconstruction using neural architecture search ensembles
Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles
R. Maulik
Romain Egele
Krishnan Raghavan
Prasanna Balaprakash
UQCV
AI4TS
AI4CE
30
6
0
20 Feb 2023
Turbulence control in plane Couette flow using low-dimensional neural
  ODE-based models and deep reinforcement learning
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
Dynamics of a data-driven low-dimensional model of turbulent minimal Couette flow
Alec J. Linot
M. Graham
AI4CE
21
18
0
11 Jan 2023
Learning Subgrid-scale Models with Neural Ordinary Differential
  Equations
Learning Subgrid-scale Models with Neural Ordinary Differential Equations
Shinhoo Kang
Emil M. Constantinescu
AI4CE
21
6
0
20 Dec 2022
Deep learning delay coordinate dynamics for chaotic attractors from
  partial observable data
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 Reduced-Order Modeling of Spatiotemporal Chaos with Neural
  Ordinary Differential Equations
Data-Driven Reduced-Order Modeling of Spatiotemporal Chaos with Neural Ordinary Differential Equations
Alec J. Linot
M. Graham
22
48
0
31 Aug 2021
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