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Physics-Informed Probabilistic Learning of Linear Embeddings of
  Non-linear Dynamics With Guaranteed Stability

Physics-Informed Probabilistic Learning of Linear Embeddings of Non-linear Dynamics With Guaranteed Stability

9 June 2019
Shaowu Pan
Karthik Duraisamy
ArXivPDFHTML

Papers citing "Physics-Informed Probabilistic Learning of Linear Embeddings of Non-linear Dynamics With Guaranteed Stability"

12 / 12 papers shown
Title
Physics-Informed Neural Networks for Enhanced Interface Preservation in Lattice Boltzmann Multiphase Simulations
Physics-Informed Neural Networks for Enhanced Interface Preservation in Lattice Boltzmann Multiphase Simulations
Yue Li
L. Zhang
AI4CE
25
1
0
13 Apr 2025
CGKN: A Deep Learning Framework for Modeling Complex Dynamical Systems and Efficient Data Assimilation
CGKN: A Deep Learning Framework for Modeling Complex Dynamical Systems and Efficient Data Assimilation
Chuanqi Chen
Nan Chen
Yinling Zhang
Jin-Long Wu
AI4CE
30
2
0
26 Oct 2024
GIT-Net: Generalized Integral Transform for Operator Learning
GIT-Net: Generalized Integral Transform for Operator Learning
Chao Wang
Alexandre H. Thiery
AI4CE
11
0
0
05 Dec 2023
Mori-Zwanzig latent space Koopman closure for nonlinear autoencoder
Mori-Zwanzig latent space Koopman closure for nonlinear autoencoder
Priyam Gupta
Peter J. Schmid
D. Sipp
T. Sayadi
Georgios Rigas
19
4
0
16 Oct 2023
Invariant preservation in machine learned PDE solvers via error
  correction
Invariant preservation in machine learned PDE solvers via error correction
N. McGreivy
Ammar Hakim
AI4CE
PINN
21
8
0
28 Mar 2023
KoopmanLab: machine learning for solving complex physics equations
KoopmanLab: machine learning for solving complex physics equations
Wei Xiong
Muyuan Ma
Xiaomeng Huang
Ziyang Zhang
Pei Sun
Yang Tian
AI4CE
22
13
0
03 Jan 2023
Transformer for Partial Differential Equations' Operator Learning
Transformer for Partial Differential Equations' Operator Learning
Zijie Li
Kazem Meidani
A. Farimani
32
140
0
26 May 2022
AutoIP: A United Framework to Integrate Physics into Gaussian Processes
AutoIP: A United Framework to Integrate Physics into Gaussian Processes
D. Long
Z. Wang
Aditi S. Krishnapriyan
Robert M. Kirby
Shandian Zhe
Michael W. Mahoney
AI4CE
10
14
0
24 Feb 2022
Diffeomorphically Learning Stable Koopman Operators
Diffeomorphically Learning Stable Koopman Operators
Petar Bevanda
Maximilian Beier
Sebastian Kerz
Armin Lederer
Stefan Sosnowski
Sandra Hirche
13
21
0
08 Dec 2021
Learning Stable Koopman Embeddings
Learning Stable Koopman Embeddings
Fletcher Fan
Bowen Yi
D. Rye
Guodong Shi
I. Manchester
25
33
0
13 Oct 2021
A purely data-driven framework for prediction, optimization, and control
  of networked processes: application to networked SIS epidemic model
A purely data-driven framework for prediction, optimization, and control of networked processes: application to networked SIS epidemic model
A. Tavasoli
T. Henry
Heman Shakeri
23
3
0
01 Aug 2021
Time-lagged autoencoders: Deep learning of slow collective variables for
  molecular kinetics
Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics
C. Wehmeyer
Frank Noé
AI4CE
BDL
109
355
0
30 Oct 2017
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