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2009.08810
Cited By
Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from Data
12 September 2020
Kadierdan Kaheman
Steven L. Brunton
J. Nathan Kutz
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Papers citing
"Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from Data"
9 / 9 papers shown
Title
Learning noise-induced transitions by multi-scaling reservoir computing
Zequn Lin
Zhaofan Lu
Zengru Di
Ying Tang
33
4
0
11 Sep 2023
Discovering Causal Relations and Equations from Data
Gustau Camps-Valls
Andreas Gerhardus
Urmi Ninad
Gherardo Varando
Georg Martius
E. Balaguer-Ballester
Ricardo Vinuesa
Emiliano Díaz
L. Zanna
Jakob Runge
PINN
AI4Cl
AI4CE
CML
40
73
0
21 May 2023
Multiphysics discovery with moving boundaries using Ensemble SINDy and Peridynamic Differential Operator
A. Bekar
E. Haghighat
E. Madenci
AI4CE
24
2
0
27 Mar 2023
Investigating Sindy As a Tool For Causal Discovery In Time Series Signals
Andrew O'Brien
Rosina O. Weber
Edward J. Kim
CML
35
6
0
29 Dec 2022
Discrepancy Modeling Framework: Learning missing physics, modeling systematic residuals, and disambiguating between deterministic and random effects
Megan R. Ebers
K. Steele
J. Nathan Kutz
37
15
0
10 Mar 2022
A Priori Denoising Strategies for Sparse Identification of Nonlinear Dynamical Systems: A Comparative Study
A. Cortiella
K. Park
Alireza Doostan
19
15
0
29 Jan 2022
Discovery of interpretable structural model errors by combining Bayesian sparse regression and data assimilation: A chaotic Kuramoto-Sivashinsky test case
R. Mojgani
Ashesh Chattopadhyay
Pedram Hassanzadeh
27
15
0
01 Oct 2021
DySMHO: Data-Driven Discovery of Governing Equations for Dynamical Systems via Moving Horizon Optimization
F. Lejarza
M. Baldea
AI4CE
27
38
0
30 Jul 2021
Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics
C. Wehmeyer
Frank Noé
AI4CE
BDL
111
356
0
30 Oct 2017
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