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Learning Physical Concepts in Cyber-Physical Systems: A Case Study

Learning Physical Concepts in Cyber-Physical Systems: A Case Study

28 November 2021
Henrik S. Steude
Alexander Windmann
Oliver Niggemann
    AI4CE
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Papers citing "Learning Physical Concepts in Cyber-Physical Systems: A Case Study"

15 / 15 papers shown
Title
Modern Koopman Theory for Dynamical Systems
Modern Koopman Theory for Dynamical Systems
Steven L. Brunton
M. Budišić
E. Kaiser
J. Nathan Kutz
AI4CE
102
417
0
24 Feb 2021
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph
  modularity
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity
S. Udrescu
A. Tan
Jiahai Feng
Orisvaldo Neto
Tailin Wu
Max Tegmark
70
191
0
18 Jun 2020
AI Feynman: a Physics-Inspired Method for Symbolic Regression
AI Feynman: a Physics-Inspired Method for Symbolic Regression
S. Udrescu
Max Tegmark
160
875
0
27 May 2019
A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis
  in Multivariate Time Series Data
A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data
Chuxu Zhang
Dongjin Song
Yuncong Chen
Xinyang Feng
C. Lumezanu
Wei Cheng
Jingchao Ni
Bo Zong
Haifeng Chen
Nitesh Chawla
AI4TS
164
700
0
20 Nov 2018
Discovering physical concepts with neural networks
Discovering physical concepts with neural networks
Raban Iten
Tony Metger
H. Wilming
L. D. Rio
R. Renner
PINN
AI4CE
55
391
0
26 Jul 2018
SOM-VAE: Interpretable Discrete Representation Learning on Time Series
SOM-VAE: Interpretable Discrete Representation Learning on Time Series
Vincent Fortuin
Matthias Huser
Francesco Locatello
Heiko Strathmann
Gunnar Rätsch
BDL
AI4TS
52
139
0
06 Jun 2018
Disentangling by Factorising
Disentangling by Factorising
Hyunjik Kim
A. Mnih
CoGe
OOD
62
1,350
0
16 Feb 2018
Isolating Sources of Disentanglement in Variational Autoencoders
Isolating Sources of Disentanglement in Variational Autoencoders
T. Chen
Xuechen Li
Roger C. Grosse
David Duvenaud
DRL
61
447
0
14 Feb 2018
UMAP: Uniform Manifold Approximation and Projection for Dimension
  Reduction
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Leland McInnes
John Healy
James Melville
160
9,432
0
09 Feb 2018
Deep learning for universal linear embeddings of nonlinear dynamics
Deep learning for universal linear embeddings of nonlinear dynamics
Bethany Lusch
J. Nathan Kutz
Steven L. Brunton
76
1,252
0
27 Dec 2017
Neural Discrete Representation Learning
Neural Discrete Representation Learning
Aaron van den Oord
Oriol Vinyals
Koray Kavukcuoglu
BDL
SSL
OCL
226
5,019
0
02 Nov 2017
InfoGAN: Interpretable Representation Learning by Information Maximizing
  Generative Adversarial Nets
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
Xi Chen
Yan Duan
Rein Houthooft
John Schulman
Ilya Sutskever
Pieter Abbeel
GAN
159
4,235
0
12 Jun 2016
Learning Phrase Representations using RNN Encoder-Decoder for
  Statistical Machine Translation
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Kyunghyun Cho
B. V. Merrienboer
Çağlar Gülçehre
Dzmitry Bahdanau
Fethi Bougares
Holger Schwenk
Yoshua Bengio
AIMat
1.0K
23,354
0
03 Jun 2014
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
452
16,929
0
20 Dec 2013
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OOD
SSL
264
12,439
0
24 Jun 2012
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