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Early Visual Concept Learning with Unsupervised Deep Learning

Early Visual Concept Learning with Unsupervised Deep Learning

17 June 2016
I. Higgins
Loic Matthey
Xavier Glorot
Arka Pal
Benigno Uria
Charles Blundell
S. Mohamed
Alexander Lerchner
    CoGe
    OCL
    DRL
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Papers citing "Early Visual Concept Learning with Unsupervised Deep Learning"

20 / 20 papers shown
Title
"Efficient Complexity": a Constrained Optimization Approach to the Evolution of Natural Intelligence
"Efficient Complexity": a Constrained Optimization Approach to the Evolution of Natural Intelligence
Serge Dolgikh
46
0
0
31 Dec 2024
Towards Learning Geometric Eigen-Lengths Crucial for Fitting Tasks
Towards Learning Geometric Eigen-Lengths Crucial for Fitting Tasks
Yijia Weng
Kaichun Mo
Ruoxi Shi
Yanchao Yang
Leonidas J. Guibas
26
3
0
25 Dec 2023
The Construction of Reality in an AI: A Review
The Construction of Reality in an AI: A Review
J. W. Johnston
3DV
13
1
0
03 Feb 2023
Blackbird's language matrices (BLMs): a new benchmark to investigate
  disentangled generalisation in neural networks
Blackbird's language matrices (BLMs): a new benchmark to investigate disentangled generalisation in neural networks
Paola Merlo
A. An
M. A. Rodriguez
28
9
0
22 May 2022
Learning to Predict Without Looking Ahead: World Models Without Forward
  Prediction
Learning to Predict Without Looking Ahead: World Models Without Forward Prediction
C. Freeman
Luke Metz
David R Ha
30
35
0
29 Oct 2019
Generalization to Novel Objects using Prior Relational Knowledge
Generalization to Novel Objects using Prior Relational Knowledge
V. Vijay
Abhinav Ganesh
Hanlin Tang
Arjun K. Bansal
GNN
19
6
0
26 Jun 2019
Affordance Learning for End-to-End Visuomotor Robot Control
Affordance Learning for End-to-End Visuomotor Robot Control
Aleksi Hämäläinen
Karol Arndt
Ali Ghadirzadeh
Ville Kyrki
38
48
0
10 Mar 2019
Semantics Preserving Adversarial Learning
Semantics Preserving Adversarial Learning
Ousmane Amadou Dia
Elnaz Barshan
Reza Babanezhad
AAML
GAN
24
2
0
10 Mar 2019
Near-Optimal Representation Learning for Hierarchical Reinforcement
  Learning
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning
Ofir Nachum
S. Gu
Honglak Lee
Sergey Levine
13
206
0
02 Oct 2018
Learning disentangled representation from 12-lead electrograms:
  application in localizing the origin of Ventricular Tachycardia
Learning disentangled representation from 12-lead electrograms: application in localizing the origin of Ventricular Tachycardia
P. Gyawali
B. Horácek
J. Sapp
Linwei Wang
30
3
0
04 Aug 2018
Curiosity Driven Exploration of Learned Disentangled Goal Spaces
Curiosity Driven Exploration of Learned Disentangled Goal Spaces
A. Laversanne-Finot
Alexandre Péré
Pierre-Yves Oudeyer
DRL
19
87
0
04 Jul 2018
xGEMs: Generating Examplars to Explain Black-Box Models
xGEMs: Generating Examplars to Explain Black-Box Models
Shalmali Joshi
Oluwasanmi Koyejo
Been Kim
Joydeep Ghosh
MLAU
25
40
0
22 Jun 2018
Stochastic Video Generation with a Learned Prior
Stochastic Video Generation with a Learned Prior
Emily L. Denton
Rob Fergus
VGen
45
525
0
21 Feb 2018
Fixing a Broken ELBO
Fixing a Broken ELBO
Alexander A. Alemi
Ben Poole
Ian S. Fischer
Joshua V. Dillon
Rif A. Saurous
Kevin Patrick Murphy
DRL
BDL
36
80
0
01 Nov 2017
Learning by Association - A versatile semi-supervised training method
  for neural networks
Learning by Association - A versatile semi-supervised training method for neural networks
Philip Häusser
A. Mordvintsev
Daniel Cremers
BDL
25
121
0
03 Jun 2017
Proximity Variational Inference
Proximity Variational Inference
Jaan Altosaar
Rajesh Ranganath
David M. Blei
BDL
6
21
0
24 May 2017
Disentangling Space and Time in Video with Hierarchical Variational
  Auto-encoders
Disentangling Space and Time in Video with Hierarchical Variational Auto-encoders
Will Grathwohl
Aaron Wilson
DRL
24
21
0
14 Dec 2016
Normalizing the Normalizers: Comparing and Extending Network
  Normalization Schemes
Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes
Mengye Ren
Renjie Liao
R. Urtasun
Fabian H. Sinz
R. Zemel
21
81
0
14 Nov 2016
Towards Deep Symbolic Reinforcement Learning
Towards Deep Symbolic Reinforcement Learning
M. Garnelo
Kai Arulkumaran
Murray Shanahan
27
225
0
18 Sep 2016
Visual Dynamics: Probabilistic Future Frame Synthesis via Cross
  Convolutional Networks
Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks
Tianfan Xue
Jiajun Wu
Katherine Bouman
Bill Freeman
43
416
0
09 Jul 2016
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