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Deep Learning for Physical Processes: Incorporating Prior Scientific
  Knowledge

Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge

21 November 2017
Emmanuel de Bézenac
Arthur Pajot
Patrick Gallinari
    PINN
    AI4CE
ArXivPDFHTML

Papers citing "Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge"

21 / 21 papers shown
Title
PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction
PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction
Hao Wu
Wei Xion
Fan Xu
Xian-Sheng Hua
C. L. Philip Chen
Xiansheng Hua
AI4TS
120
28
0
19 May 2023
Numerical Gaussian Processes for Time-dependent and Non-linear Partial
  Differential Equations
Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
M. Raissi
P. Perdikaris
George Karniadakis
53
267
0
29 Mar 2017
Guided Optical Flow Learning
Guided Optical Flow Learning
Yi Zhu
Zhenzhong Lan
Shawn D. Newsam
Alexander G. Hauptmann
SSL
54
48
0
08 Feb 2017
Transformation-Based Models of Video Sequences
Transformation-Based Models of Video Sequences
Joost R. van Amersfoort
A. Kannan
MarcÁurelio Ranzato
Arthur Szlam
Du Tran
Soumith Chintala
ViT
39
76
0
29 Jan 2017
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
Eddy Ilg
N. Mayer
Tonmoy Saikia
Margret Keuper
Alexey Dosovitskiy
Thomas Brox
3DPC
189
3,072
0
06 Dec 2016
Video Pixel Networks
Video Pixel Networks
Nal Kalchbrenner
Aaron van den Oord
Karen Simonyan
Ivo Danihelka
Oriol Vinyals
Alex Graves
Koray Kavukcuoglu
56
423
0
03 Oct 2016
Back to Basics: Unsupervised Learning of Optical Flow via Brightness
  Constancy and Motion Smoothness
Back to Basics: Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness
Jason J. Yu
Adam W. Harley
Konstantinos G. Derpanis
48
406
0
20 Aug 2016
Accelerating Eulerian Fluid Simulation With Convolutional Networks
Accelerating Eulerian Fluid Simulation With Convolutional Networks
Jonathan Tompson
Kristofer Schlachter
Pablo Sprechmann
Ken Perlin
75
530
0
13 Jul 2016
An Uncertain Future: Forecasting from Static Images using Variational
  Autoencoders
An Uncertain Future: Forecasting from Static Images using Variational Autoencoders
Jacob Walker
Carl Doersch
Abhinav Gupta
M. Hebert
VGen
33
513
0
25 Jun 2016
Unsupervised Learning for Physical Interaction through Video Prediction
Unsupervised Learning for Physical Interaction through Video Prediction
Chelsea Finn
Ian Goodfellow
Sergey Levine
62
1,042
0
23 May 2016
Deep Variational Bayes Filters: Unsupervised Learning of State Space
  Models from Raw Data
Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data
Maximilian Karl
Maximilian Sölch
Justin Bayer
Patrick van der Smagt
BDL
38
373
0
20 May 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
1.4K
192,638
0
10 Dec 2015
Spatio-temporal video autoencoder with differentiable memory
Spatio-temporal video autoencoder with differentiable memory
Viorica Patraucean
Ankur Handa
R. Cipolla
63
307
0
19 Nov 2015
Deep multi-scale video prediction beyond mean square error
Deep multi-scale video prediction beyond mean square error
Michaël Mathieu
Camille Couprie
Yann LeCun
GAN
107
1,880
0
17 Nov 2015
Deep Kalman Filters
Deep Kalman Filters
Rahul G. Krishnan
Uri Shalit
David Sontag
BDL
AI4TS
56
372
0
16 Nov 2015
Convolutional LSTM Network: A Machine Learning Approach for
  Precipitation Nowcasting
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Xingjian Shi
Zhourong Chen
Hao Wang
Dit-Yan Yeung
W. Wong
W. Woo
471
7,952
0
13 Jun 2015
A Recurrent Latent Variable Model for Sequential Data
A Recurrent Latent Variable Model for Sequential Data
Junyoung Chung
Kyle Kastner
Laurent Dinh
Kratarth Goel
Aaron Courville
Yoshua Bengio
DRL
BDL
70
1,250
0
07 Jun 2015
Spatial Transformer Networks
Spatial Transformer Networks
Max Jaderberg
Karen Simonyan
Andrew Zisserman
Koray Kavukcuoglu
264
7,361
0
05 Jun 2015
FlowNet: Learning Optical Flow with Convolutional Networks
FlowNet: Learning Optical Flow with Convolutional Networks
Philipp Fischer
Alexey Dosovitskiy
Eddy Ilg
Philip Häusser
C. Hazirbas
Vladimir Golkov
Patrick van der Smagt
Daniel Cremers
Thomas Brox
3DPC
254
4,159
0
26 Apr 2015
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
367
16,962
0
20 Dec 2013
Linear Latent Force Models using Gaussian Processes
Linear Latent Force Models using Gaussian Processes
Mauricio A. Alvarez
D. Luengo
Neil D. Lawrence
49
124
0
13 Jul 2011
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