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1804.03599
Cited By
Understanding disentangling in
β
β
β
-VAE
10 April 2018
Christopher P. Burgess
I. Higgins
Arka Pal
Loic Matthey
Nicholas Watters
Guillaume Desjardins
Alexander Lerchner
CoGe
DRL
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Papers citing
"Understanding disentangling in $β$-VAE"
37 / 37 papers shown
Title
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Paresh Chaudhary
Yancheng Liang
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Learning Metal Microstructural Heterogeneity through Spatial Mapping of Diffraction Latent Space Features
Mathieu Calvat
Chris Bean
Dhruv Anjaria
Hyoungryul Park
Haoren Wang
Kenneth Vecchio
J.C. Stinville
AI4CE
79
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30 Jan 2025
Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations
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Johannes Brunnemann
Jörg Eiden
Arne Speerforck
Lars Mikelsons
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14 Oct 2024
PECAN: Personalizing Robot Behaviors through a Learned Canonical Space
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Robert Ramirez Sanchez
Dylan P. Losey
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22 Jul 2024
Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models
Samuel Marks
Can Rager
Eric J. Michaud
Yonatan Belinkov
David Bau
Aaron Mueller
131
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28 Mar 2024
Disentanglement Learning via Topology
Nikita Balabin
Daria Voronkova
I. Trofimov
Evgeny Burnaev
S. Barannikov
DRL
101
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0
24 Aug 2023
LatentGAN Autoencoder: Learning Disentangled Latent Distribution
Sanket Kalwar
Animikh Aich
Tanay Dixit
Adit Chhabra
DRL
59
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0
05 Apr 2022
Linear Disentangled Representations and Unsupervised Action Estimation
Matthew Painter
Jonathon S. Hare
Adam Prugel-Bennett
CoGe
DRL
66
20
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18 Aug 2020
PCAAE: Principal Component Analysis Autoencoder for organising the latent space of generative networks
Chi-Hieu Pham
Saïd Ladjal
A. Newson
DRL
74
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14 Jun 2020
DARLA: Improving Zero-Shot Transfer in Reinforcement Learning
I. Higgins
Arka Pal
Andrei A. Rusu
Loic Matthey
Christopher P. Burgess
Alexander Pritzel
M. Botvinick
Charles Blundell
Alexander Lerchner
DRL
104
415
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26 Jul 2017
SCAN: Learning Hierarchical Compositional Visual Concepts
I. Higgins
Nicolas Sonnerat
Loic Matthey
Arka Pal
Christopher P. Burgess
Matko Bosnjak
Murray Shanahan
M. Botvinick
Demis Hassabis
Alexander Lerchner
OCL
DRL
CoGe
57
51
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11 Jul 2017
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
247
2,963
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20 Mar 2017
A Survey of Inductive Biases for Factorial Representation-Learning
Karl Ridgeway
DRL
CML
60
76
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15 Dec 2016
Deep Variational Information Bottleneck
Alexander A. Alemi
Ian S. Fischer
Joshua V. Dillon
Kevin Patrick Murphy
119
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0
01 Dec 2016
Reinforcement Learning with Unsupervised Auxiliary Tasks
Max Jaderberg
Volodymyr Mnih
Wojciech M. Czarnecki
Tom Schaul
Joel Z Leibo
David Silver
Koray Kavukcuoglu
SSL
101
1,228
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16 Nov 2016
Information Dropout: Learning Optimal Representations Through Noisy Computation
Alessandro Achille
Stefano Soatto
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SSL
57
401
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04 Nov 2016
WaveNet: A Generative Model for Raw Audio
Aaron van den Oord
Sander Dieleman
Heiga Zen
Karen Simonyan
Oriol Vinyals
Alex Graves
Nal Kalchbrenner
A. Senior
Koray Kavukcuoglu
DiffM
406
7,391
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12 Sep 2016
Conditional Image Generation with PixelCNN Decoders
Aaron van den Oord
Nal Kalchbrenner
Oriol Vinyals
L. Espeholt
Alex Graves
Koray Kavukcuoglu
VLM
204
2,511
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16 Jun 2016
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
Xi Chen
Yan Duan
Rein Houthooft
John Schulman
Ilya Sutskever
Pieter Abbeel
GAN
157
4,235
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12 Jun 2016
Understanding Visual Concepts with Continuation Learning
William F. Whitney
Michael Chang
Tejas D. Kulkarni
J. Tenenbaum
DRL
GAN
76
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22 Feb 2016
Asynchronous Methods for Deep Reinforcement Learning
Volodymyr Mnih
Adria Puigdomenech Badia
M. Berk Mirza
Alex Graves
Timothy Lillicrap
Tim Harley
David Silver
Koray Kavukcuoglu
197
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04 Feb 2016
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis
Jimei Yang
Scott E. Reed
Ming-Hsuan Yang
Honglak Lee
VOT
58
314
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05 Jan 2016
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
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193,878
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10 Dec 2015
Bayesian representation learning with oracle constraints
Theofanis Karaletsos
Serge J. Belongie
Gunnar Rätsch
BDL
55
92
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16 Jun 2015
Learning to Linearize Under Uncertainty
Ross Goroshin
Michaël Mathieu
Yann LeCun
GAN
OOD
89
141
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09 Jun 2015
Deep Convolutional Inverse Graphics Network
Tejas D. Kulkarni
William F. Whitney
Pushmeet Kohli
J. Tenenbaum
DRL
BDL
103
929
0
11 Mar 2015
DRAW: A Recurrent Neural Network For Image Generation
Karol Gregor
Ivo Danihelka
Alex Graves
Danilo Jimenez Rezende
Daan Wierstra
GAN
DRL
163
1,962
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16 Feb 2015
Transformation Properties of Learned Visual Representations
Taco S. Cohen
Max Welling
49
106
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24 Dec 2014
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
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150,039
0
22 Dec 2014
Discovering Hidden Factors of Variation in Deep Networks
Brian Cheung
J. Livezey
Arjun K. Bansal
Bruno A. Olshausen
DRL
74
193
0
20 Dec 2014
Going Deeper with Convolutions
Christian Szegedy
Wei Liu
Yangqing Jia
P. Sermanet
Scott E. Reed
Dragomir Anguelov
D. Erhan
Vincent Vanhoucke
Andrew Rabinovich
460
43,649
0
17 Sep 2014
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
452
16,933
0
20 Dec 2013
High-Dimensional Probability Estimation with Deep Density Models
Oren Rippel
Ryan P. Adams
163
124
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20 Feb 2013
Disentangling Factors of Variation via Generative Entangling
Guillaume Desjardins
Aaron Courville
Yoshua Bengio
CoGe
CML
DRL
90
104
0
19 Oct 2012
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OOD
SSL
256
12,435
0
24 Jun 2012
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