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Learning Variational Data Assimilation Models and Solvers

Learning Variational Data Assimilation Models and Solvers

25 July 2020
Ronan Fablet
Bertrand Chapron
Lucas Drumetz
É. Mémin
O. Pannekoucke
F. Rousseau
ArXiv (abs)PDFHTML

Papers citing "Learning Variational Data Assimilation Models and Solvers"

14 / 14 papers shown
Title
Meta-Learning in Neural Networks: A Survey
Meta-Learning in Neural Networks: A Survey
Timothy M. Hospedales
Antreas Antoniou
P. Micaelli
Amos Storkey
OOD
393
1,979
0
11 Apr 2020
PDE-NetGen 1.0: from symbolic PDE representations of physical processes
  to trainable neural network representations
PDE-NetGen 1.0: from symbolic PDE representations of physical processes to trainable neural network representations
O. Pannekoucke
Ronan Fablet
AI4CEPINNDiffM
31
8
0
03 Feb 2020
Bayesian inference of chaotic dynamics by merging data assimilation,
  machine learning and expectation-maximization
Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization
Marc Bocquet
J. Brajard
A. Carrassi
Laurent Bertino
56
104
0
17 Jan 2020
End-to-end learning of energy-based representations for
  irregularly-sampled signals and images
End-to-end learning of energy-based representations for irregularly-sampled signals and images
Ronan Fablet
Lucas Drumetz
F. Rousseau
AI4TS
18
7
0
01 Oct 2019
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
417
5,111
0
19 Jun 2018
DeepISP: Towards Learning an End-to-End Image Processing Pipeline
DeepISP: Towards Learning an End-to-End Image Processing Pipeline
Eli Schwartz
Raja Giryes
A. Bronstein
VLM
72
227
0
20 Jan 2018
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial
  Differential Equations
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
M. Raissi
PINNAI4CE
120
755
0
20 Jan 2018
Bilinear residual Neural Network for the identification and forecasting
  of dynamical systems
Bilinear residual Neural Network for the identification and forecasting of dynamical systems
Ronan Fablet
Said Ouala
Cédric Herzet
AI4TS
38
45
0
19 Dec 2017
A Review of Convolutional Neural Networks for Inverse Problems in
  Imaging
A Review of Convolutional Neural Networks for Inverse Problems in Imaging
Michael T. McCann
Kyong Hwan Jin
M. Unser
3DV
61
593
0
11 Oct 2017
Learning to Generalize: Meta-Learning for Domain Generalization
Learning to Generalize: Meta-Learning for Domain Generalization
Da Li
Yongxin Yang
Yi-Zhe Song
Timothy M. Hospedales
OOD
102
1,421
0
10 Oct 2017
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
Özgün Çiçek
Ahmed Abdulkadir
S. Lienkamp
Thomas Brox
Olaf Ronneberger
3DV3DPCSSeg3DH
152
6,537
0
21 Jun 2016
Learning to learn by gradient descent by gradient descent
Learning to learn by gradient descent by gradient descent
Marcin Andrychowicz
Misha Denil
Sergio Gomez Colmenarejo
Matthew W. Hoffman
David Pfau
Tom Schaul
Brendan Shillingford
Nando de Freitas
113
2,006
0
14 Jun 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,020
0
10 Dec 2015
On learning optimized reaction diffusion processes for effective image
  restoration
On learning optimized reaction diffusion processes for effective image restoration
Yunjin Chen
Wei Yu
Thomas Pock
DiffM
54
323
0
19 Mar 2015
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