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Learning Interpretable Shapelets for Time Series Classification through
  Adversarial Regularization

Learning Interpretable Shapelets for Time Series Classification through Adversarial Regularization

3 June 2019
Yichang Wang
Rémi Emonet
Elisa Fromont
S. Malinowski
Etienne Ménager
Loic Mosser
R. Tavenard
    AI4TS
ArXivPDFHTML

Papers citing "Learning Interpretable Shapelets for Time Series Classification through Adversarial Regularization"

7 / 7 papers shown
Title
Deep learning for time series classification: a review
Deep learning for time series classification: a review
Hassan Ismail Fawaz
Germain Forestier
J. Weber
L. Idoumghar
Pierre-Alain Muller
AI4TS
AI4CE
283
2,683
0
12 Sep 2018
A Survey Of Methods For Explaining Black Box Models
A Survey Of Methods For Explaining Black Box Models
Riccardo Guidotti
A. Monreale
Salvatore Ruggieri
Franco Turini
D. Pedreschi
F. Giannotti
XAI
120
3,938
0
06 Feb 2018
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
889
21,815
0
22 May 2017
Improved Training of Wasserstein GANs
Improved Training of Wasserstein GANs
Ishaan Gulrajani
Faruk Ahmed
Martín Arjovsky
Vincent Dumoulin
Aaron Courville
GAN
173
9,533
0
31 Mar 2017
Adversarial Discriminative Domain Adaptation
Adversarial Discriminative Domain Adaptation
Eric Tzeng
Judy Hoffman
Kate Saenko
Trevor Darrell
GAN
OOD
257
4,655
0
17 Feb 2017
Time Series Classification from Scratch with Deep Neural Networks: A
  Strong Baseline
Time Series Classification from Scratch with Deep Neural Networks: A Strong Baseline
Zhiguang Wang
Weizhong Yan
Tim Oates
AI4TS
60
1,652
0
20 Nov 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
943
16,931
0
16 Feb 2016
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