UB Paderborn / Katalog / Suche / in CDI

Sortiert nach

Einfacher Volltextzugriff von (fast) überall

Installieren Sie die LibKey Nomad-Browsererweiterung und erhalten Sie von vielen Webseiten einfachen Zugriff auf lizenzierte Volltexte oder Open Access Publikationen. Mehr erfahren...

Deep learning in fluid dynamics

Journal of fluid mechanics, 2017-03, Vol.814, p.1-4

Kutz, J. Nathan

2017

Volltextzugriff (PDF)

Data-driven discovery of coordinates and governing equations

Proceedings of the National Academy of Sciences - PNAS, 2019-11, Vol.116 (45), p.22445-22451

2019

Volltextzugriff (PDF)

Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control

1, 2019

Volltextzugriff (PDF)

Deep learning for universal linear embeddings of nonlinear dynamics

Nature communications, 2018-11, Vol.9 (1), p.4950-10, Article 4950

2018

Volltextzugriff (PDF)

Sparse identification of nonlinear dynamics for rapid model recovery

Chaos (Woodbury, N.Y.), 2018-06, Vol.28 (6)

2018

Volltextzugriff (PDF)

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

Proceedings of the National Academy of Sciences - PNAS, 2016-04, Vol.113 (15), p.3932-3937

2016

Volltextzugriff (PDF)

Chaos as an intermittently forced linear system

Nature communications, 2017-05, Vol.8 (1), p.19-19, Article 19

2017

Volltextzugriff (PDF)

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

Journal of computational physics, 2019-11, Vol.396, p.483-506

2019

Volltextzugriff (PDF)

Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning

AIAA journal, 2021-08, p.1-26

2021

Volltextzugriff (PDF)

DeepGreen: deep learning of Green’s functions for nonlinear boundary value problems

Scientific reports, 2021-11, Vol.11 (1), p.21614-21614, Article 21614

2021

Volltextzugriff (PDF)

Data-driven discovery of Koopman eigenfunctions for control

Machine learning: science and technology, 2021-09, Vol.2 (3), p.35023

2021

Volltextzugriff (PDF)

Extracting spatial–temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition

Journal of neuroscience methods, 2016-01, Vol.258, p.1-15

2016

Volltextzugriff (PDF)

Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control

PloS one, 2016-02, Vol.11 (2), p.e0150171-e0150171

2016

Volltextzugriff (PDF)

Forecasting dengue fever in Brazil: An assessment of climate conditions

PloS one, 2019-08, Vol.14 (8), p.e0220106-e0220106

2019

Volltextzugriff (PDF)

Learning dominant physical processes with data-driven balance models

Nature communications, 2021-02, Vol.12 (1), p.1016-1016, Article 1016

2021

Volltextzugriff (PDF)

Greedy Sensor Placement With Cost Constraints

IEEE sensors journal, 2019-04, Vol.19 (7), p.2642-2656

2019

Volltextzugriff (PDF)

Generalizing Koopman Theory to Allow for Inputs and Control

SIAM journal on applied dynamical systems, 2018, Vol.17 (1), p.909-930

2018

Volltextzugriff (PDF)

Optimal Sensor and Actuator Selection Using Balanced Model Reduction

IEEE transactions on automatic control, 2022-04, Vol.67 (4), p.2108-2115

2022

Volltextzugriff (PDF)

Dynamic Mode Decomposition for Compressive System Identification

AIAA journal, 2020-02, Vol.58 (2), p.561-574

2020

Volltextzugriff (PDF)

A Unified Framework for Sparse Relaxed Regularized Regression: SR3

IEEE access, 2019, Vol.7, p.1404-1423

2019

Volltextzugriff (PDF)

Automatic differentiation to simultaneously identify nonlinear dynamics and extract noise probability distributions from data

Machine learning: science and technology, 2022-03, Vol.3 (1), p.15031

2022

Volltextzugriff (PDF)

Computing spectra of linear operators using the Floquet–Fourier–Hill method

Journal of computational physics, 2006-11, Vol.219 (1), p.296-321

2006

Volltextzugriff (PDF)

Applied Koopman Theory for Partial Differential Equations and Data-Driven Modeling of Spatio-Temporal Systems

Complexity (New York, N.Y.), 2018-01, Vol.2018 (2018), p.1-16

2018

Volltextzugriff (PDF)

Dissipative soliton resonance in a passively mode-locked fiber laser

Optics letters, 2011-04, Vol.36 (7), p.1146

2011

Volltextzugriff (PDF)

A Unified Sparse Optimization Framework to Learn Parsimonious Physics-Informed Models From Data

IEEE access, 2020, Vol.8, p.169259-169271

2020

Volltextzugriff (PDF)

1 – 25 von 414

Suche als RSS-Feed

Suchergebnisse filtern

Filter anzeigen

Nur zeigen

Geprüft (Peer-Review)
(332)
Mit Volltextzugriff
(342)

Publikationsform

1 weiteren anzeigen...

Weniger anzeigen...

Sprache

Englisch
(414)
Japanisch
(1)

Erscheinungsjahr

n.n

Thema

Science & Technology
(331)
Physical Sciences
(224)
Physics
(152)
Technology
(119)
Optics
(108)
Engineering
(92)
Mathematics
(72)
Physics, Mathematical
(67)
Computer Science
(57)
Engineering, Electrical & Electronic
(56)
Mathematics, Applied
(56)
Machine Learning
(52)
Dynamical Systems
(45)
Algorithms
(43)
Science & Technology - Other Topics
(40)
Multidisciplinary Sciences
(39)
Life Sciences & Biomedicine
(37)
Mathematical Models
(37)
Exact Sciences And Technology
(36)
Physics, Applied
(30)

15 weitere anzeigen...

Weniger anzeigen...

Neu hinzugefügt

... seit 90 Tagen
(7)

Menü

Weitere Dienste

Einstellungen

Deep learning in fluid dynamics

Data-driven discovery of coordinates and governing equations

Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control

Deep learning for universal linear embeddings of nonlinear dynamics

Sparse identification of nonlinear dynamics for rapid model recovery

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

Chaos as an intermittently forced linear system

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

Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning

DeepGreen: deep learning of Green’s functions for nonlinear boundary value problems

Data-driven discovery of Koopman eigenfunctions for control

Extracting spatial–temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition

Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control

Forecasting dengue fever in Brazil: An assessment of climate conditions

Learning dominant physical processes with data-driven balance models

Greedy Sensor Placement With Cost Constraints

Generalizing Koopman Theory to Allow for Inputs and Control

Optimal Sensor and Actuator Selection Using Balanced Model Reduction

Dynamic Mode Decomposition for Compressive System Identification

A Unified Framework for Sparse Relaxed Regularized Regression: SR3

Automatic differentiation to simultaneously identify nonlinear dynamics and extract noise probability distributions from data

Computing spectra of linear operators using the Floquet–Fourier–Hill method

Applied Koopman Theory for Partial Differential Equations and Data-Driven Modeling of Spatio-Temporal Systems

Dissipative soliton resonance in a passively mode-locked fiber laser

A Unified Sparse Optimization Framework to Learn Parsimonious Physics-Informed Models From Data

Suchergebnisse filtern