A Review of Data‐Driven Discovery for Dynamic Systems (Q6131430)

scientific article; zbMATH DE number 7827691

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English	A Review of Data‐Driven Discovery for Dynamic Systems	scientific article; zbMATH DE number 7827691

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instance of

scholarly article

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title

A Review of Data‐Driven Discovery for Dynamic Systems (English)

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International Statistical Review

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publication date

5 April 2024

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full work available at URL

https://arxiv.org/abs/2210.10663

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zbMATH Keywords

differential equations

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dynamic equation discovery

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probabilistic dynamic equation discovery

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MaRDI profile type

MaRDI publication profile

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cites work

Q4377005

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Automated reverse engineering of nonlinear dynamical systems

0 references

DeepMoD: deep learning for model discovery in noisy data

0 references

Discovering governing equations from data by sparse identification of nonlinear dynamical systems

0 references

The horseshoe estimator for sparse signals

0 references

Data-driven discovery of coordinates and governing equations

0 references

Numerical differentiation of noisy, nonsmooth data

0 references

Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting

0 references

Proximal Splitting Methods in Signal Processing

0 references

Q3058567

0 references

Q3119169

0 references

Q4344410

0 references

Physically motivated scale interaction parameterization in reduced rank quadratic nonlinear dynamic spatio‐temporal models

0 references

The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo

0 references

Multilayer feedforward networks are universal approximators

0 references

Ensemble Kalman Methods for High-Dimensional Hierarchical Dynamic Space-Time Models

0 references

Solving parametric PDE problems with artificial neural networks

0 references

Q5409194

0 references

Learning partial differential equations for biological transport models from noisy spatio-temporal data

0 references

The Bayesian elastic net

0 references

PDE-Net 2.0: learning PDEs from data with a numeric-symbolic hybrid deep network

0 references

The Group Lasso for Logistic Regression

0 references

Bayesian Variable Selection in Linear Regression

0 references

The Bayesian Lasso

0 references

Sparsity information and regularization in the horseshoe and other shrinkage priors

0 references

Data driven governing equations approximation using deep neural networks

0 references

Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations

0 references

Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

0 references

Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations

0 references

Q4250336

0 references

Data-Driven Identification of Parametric Partial Differential Equations

0 references

Deep learning of dynamics and signal-noise decomposition with time-stepping constraints

0 references

Learning partial differential equations via data discovery and sparse optimization

0 references

Runge-Kutta pairs of order \(5(4)\) satisfying only the first column simplifying assumption

0 references

Sparse dynamical system identification with simultaneous structural parameters and initial condition estimation

0 references

Polynomial nonlinear spatio‐temporal integro‐difference equation models

0 references

A general science-based framework for dynamical spatio-temporal models

0 references

Spatiotemporal Hierarchical Bayesian Modeling Tropical Ocean Surface Winds

0 references

Numerical aspects for approximating governing equations using data

0 references

Data-driven deep learning of partial differential equations in modal space

0 references

DL-PDE: Deep-Learning Based Data-Driven Discovery of Partial Differential Equations from Discrete and Noisy Data

0 references

DLGA-PDE: discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm

0 references

Bayesian differential programming for robust systems identification under uncertainty

0 references

Deep Compositional Spatial Models

0 references

Robust data-driven discovery of governing physical laws with error bars

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On the Convergence of the SINDy Algorithm

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Identifiers

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Mathematics Subject Classification ID

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Sitelinks

Mathematics(1 entry)

mardi Publication:6131430