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2008.10740
Cited By
Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning
24 August 2020
Steven L. Brunton
J. Nathan Kutz
Krithika Manohar
Aleksandr Aravkin
K. Morgansen
Jennifer Klemisch
Nicholas Goebel
J. Buttrick
Jeffrey Poskin
Agnes Blom-Schieber
Thomas Hogan
Darren McDonald
AI4CE
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Papers citing
"Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning"
7 / 7 papers shown
Title
Aerodynamic and structural airfoil shape optimisation via Transfer Learning-enhanced Deep Reinforcement Learning
David Ramos
Lucas Lacasa
E. Valero
G. Rubio
AI4CE
27
0
0
05 May 2025
Learning Interpretable Models of Aircraft Handling Behaviour by Reinforcement Learning from Human Feedback
Tom Bewley
J. Lawry
Arthur G. Richards
30
1
0
26 May 2023
The transformative potential of machine learning for experiments in fluid mechanics
Ricardo Vinuesa
Steven L. Brunton
B. McKeon
AI4CE
24
68
0
28 Mar 2023
Lagrangian Neural Networks
M. Cranmer
S. Greydanus
Stephan Hoyer
Peter W. Battaglia
D. Spergel
S. Ho
PINN
130
424
0
10 Mar 2020
Learning Symbolic Physics with Graph Networks
M. Cranmer
Rui Xu
Peter W. Battaglia
S. Ho
PINN
AI4CE
185
83
0
12 Sep 2019
Generalized Kalman Smoothing: Modeling and Algorithms
Aleksandr Aravkin
J. Burke
L. Ljung
A. Lozano
G. Pillonetto
76
111
0
20 Sep 2016
An algorithm for the principal component analysis of large data sets
N. Halko
P. Martinsson
Y. Shkolnisky
M. Tygert
60
277
0
30 Jul 2010
1