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Unsupervised state representation learning with robotic priors: a
  robustness benchmark

Unsupervised state representation learning with robotic priors: a robustness benchmark

15 September 2017
Timothée Lesort
Mathieu Seurin
Xinrui Li
Natalia Díaz Rodríguez
David Filliat
    SSL
    DRL
ArXivPDFHTML

Papers citing "Unsupervised state representation learning with robotic priors: a robustness benchmark"

11 / 11 papers shown
Title
PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured
  State Representations
PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations
Rico Jonschkowski
Roland Hafner
Jonathan Scholz
Martin Riedmiller
45
67
0
27 May 2017
Domain Randomization for Transferring Deep Neural Networks from
  Simulation to the Real World
Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World
Joshua Tobin
Rachel Fong
Alex Ray
Jonas Schneider
Wojciech Zaremba
Pieter Abbeel
244
2,963
0
20 Mar 2017
The Curious Robot: Learning Visual Representations via Physical
  Interactions
The Curious Robot: Learning Visual Representations via Physical Interactions
Lerrel Pinto
Dhiraj Gandhi
Yuanfeng Han
Yong‐Lae Park
Abhinav Gupta
83
186
0
05 Apr 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
193,878
0
10 Dec 2015
Deep Spatial Autoencoders for Visuomotor Learning
Deep Spatial Autoencoders for Visuomotor Learning
Chelsea Finn
X. Tan
Yan Duan
Trevor Darrell
Sergey Levine
Pieter Abbeel
SSL
56
552
0
21 Sep 2015
Embed to Control: A Locally Linear Latent Dynamics Model for Control
  from Raw Images
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images
Manuel Watter
Jost Tobias Springenberg
Joschka Boedecker
Martin Riedmiller
BDL
68
845
0
24 Jun 2015
Learning to Linearize Under Uncertainty
Learning to Linearize Under Uncertainty
Ross Goroshin
Michaël Mathieu
Yann LeCun
GAN
OOD
86
141
0
09 Jun 2015
Predictive State Representations: A New Theory for Modeling Dynamical
  Systems
Predictive State Representations: A New Theory for Modeling Dynamical Systems
Satinder Singh
Michael R. James
Matthew R. Rudary
AI4TS
AI4CE
86
289
0
11 Jul 2012
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OOD
SSL
256
12,435
0
24 Jun 2012
A new embedding quality assessment method for manifold learning
A new embedding quality assessment method for manifold learning
Peng Zhang
Yuanyuan Ren
Bo Zhang
85
30
0
08 Aug 2011
Closing the Learning-Planning Loop with Predictive State Representations
Closing the Learning-Planning Loop with Predictive State Representations
Byron Boots
S. Siddiqi
Geoffrey J. Gordon
236
265
0
12 Dec 2009
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