ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2009.06795
  4. Cited By
DynamicVAE: Decoupling Reconstruction Error and Disentangled
  Representation Learning

DynamicVAE: Decoupling Reconstruction Error and Disentangled Representation Learning

15 September 2020
Huajie Shao
Haohong Lin
Qinmin Yang
Shuochao Yao
Han Zhao
Tarek Abdelzaher
    DRL
ArXivPDFHTML

Papers citing "DynamicVAE: Decoupling Reconstruction Error and Disentangled Representation Learning"

28 / 28 papers shown
Title
Generative Adversarial Networks
Generative Adversarial Networks
Gilad Cohen
Raja Giryes
GAN
194
30,069
0
01 Mar 2022
Responsive Safety in Reinforcement Learning by PID Lagrangian Methods
Responsive Safety in Reinforcement Learning by PID Lagrangian Methods
Adam Stooke
Joshua Achiam
Pieter Abbeel
53
291
0
08 Jul 2020
Semi-Supervised StyleGAN for Disentanglement Learning
Semi-Supervised StyleGAN for Disentanglement Learning
Weili Nie
Tero Karras
Animesh Garg
Shoubhik Debhath
Anjul Patney
Ankit B. Patel
Anima Anandkumar
DRL
114
72
0
06 Mar 2020
Weakly-Supervised Disentanglement Without Compromises
Weakly-Supervised Disentanglement Without Compromises
Francesco Locatello
Ben Poole
Gunnar Rätsch
Bernhard Schölkopf
Olivier Bachem
Michael Tschannen
CoGe
OOD
DRL
212
315
0
07 Feb 2020
Weakly Supervised Disentanglement with Guarantees
Weakly Supervised Disentanglement with Guarantees
Rui Shu
Yining Chen
Abhishek Kumar
Stefano Ermon
Ben Poole
CoGe
DRL
100
137
0
22 Oct 2019
Deep Learning Theory Review: An Optimal Control and Dynamical Systems
  Perspective
Deep Learning Theory Review: An Optimal Control and Dynamical Systems Perspective
Guan-Horng Liu
Evangelos A. Theodorou
AI4CE
46
71
0
28 Aug 2019
Theory and Evaluation Metrics for Learning Disentangled Representations
Theory and Evaluation Metrics for Learning Disentangled Representations
Kien Do
T. Tran
CoGe
DRL
44
95
0
26 Aug 2019
Weakly Supervised Disentanglement by Pairwise Similarities
Weakly Supervised Disentanglement by Pairwise Similarities
Junxiang Chen
Kayhan Batmanghelich
CoGe
DRL
28
53
0
03 Jun 2019
On the Fairness of Disentangled Representations
On the Fairness of Disentangled Representations
Francesco Locatello
G. Abbati
Tom Rainforth
Stefan Bauer
Bernhard Schölkopf
Olivier Bachem
FaML
DRL
61
226
0
31 May 2019
Are Disentangled Representations Helpful for Abstract Visual Reasoning?
Are Disentangled Representations Helpful for Abstract Visual Reasoning?
Sjoerd van Steenkiste
Francesco Locatello
Jürgen Schmidhuber
Olivier Bachem
71
208
0
29 May 2019
Disentangling Factors of Variation Using Few Labels
Disentangling Factors of Variation Using Few Labels
Francesco Locatello
Michael Tschannen
Stefan Bauer
Gunnar Rätsch
Bernhard Schölkopf
Olivier Bachem
DRL
CML
CoGe
62
123
0
03 May 2019
Towards a Definition of Disentangled Representations
Towards a Definition of Disentangled Representations
I. Higgins
David Amos
David Pfau
S. Racanière
Loic Matthey
Danilo Jimenez Rezende
Alexander Lerchner
OCL
DRL
92
475
0
05 Dec 2018
Challenging Common Assumptions in the Unsupervised Learning of
  Disentangled Representations
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
Francesco Locatello
Stefan Bauer
Mario Lucic
Gunnar Rätsch
Sylvain Gelly
Bernhard Schölkopf
Olivier Bachem
OOD
104
1,451
0
29 Nov 2018
Understanding disentangling in $β$-VAE
Understanding disentangling in βββ-VAE
Christopher P. Burgess
I. Higgins
Arka Pal
Loic Matthey
Nicholas Watters
Guillaume Desjardins
Alexander Lerchner
CoGe
DRL
52
828
0
10 Apr 2018
Disentangling by Factorising
Disentangling by Factorising
Hyunjik Kim
A. Mnih
CoGe
OOD
54
1,336
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
43
449
0
14 Feb 2018
Building machines that adapt and compute like brains
Building machines that adapt and compute like brains
Brenden M. Lake
J. Tenenbaum
AI4CE
FedML
NAI
AILaw
317
886
0
11 Nov 2017
Variational Inference of Disentangled Latent Concepts from Unlabeled
  Observations
Variational Inference of Disentangled Latent Concepts from Unlabeled Observations
Abhishek Kumar
P. Sattigeri
Avinash Balakrishnan
BDL
DRL
71
520
0
02 Nov 2017
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised
  Learning
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning
Marco Fraccaro
Simon Kamronn
Ulrich Paquet
Ole Winther
BDL
51
283
0
16 Oct 2017
Learning Disentangled Representations with Semi-Supervised Deep
  Generative Models
Learning Disentangled Representations with Semi-Supervised Deep Generative Models
Siddharth Narayanaswamy
Brooks Paige
Jan-Willem van de Meent
Alban Desmaison
Noah D. Goodman
Pushmeet Kohli
Frank Wood
Philip Torr
DRL
CoGe
113
359
0
01 Jun 2017
Unsupervised Learning of Disentangled Representations from Video
Unsupervised Learning of Disentangled Representations from Video
Emily L. Denton
Vighnesh Birodkar
DRL
CoGe
OOD
73
552
0
31 May 2017
Multi-Level Variational Autoencoder: Learning Disentangled
  Representations from Grouped Observations
Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations
Diane Bouchacourt
Ryota Tomioka
Sebastian Nowozin
BDL
OOD
DRL
52
310
0
24 May 2017
Disentangling factors of variation in deep representations using
  adversarial training
Disentangling factors of variation in deep representations using adversarial training
Michaël Mathieu
Jiaqi Zhao
Pablo Sprechmann
Aditya A. Ramesh
Yann LeCun
DRL
CML
87
490
0
10 Nov 2016
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
148
4,224
0
12 Jun 2016
Weakly-supervised Disentangling with Recurrent Transformations for 3D
  View Synthesis
Weakly-supervised Disentangling with Recurrent Transformations for 3D View Synthesis
Jimei Yang
Scott E. Reed
Ming-Hsuan Yang
Honglak Lee
VOT
42
314
0
05 Jan 2016
Semi-Supervised Learning with Deep Generative Models
Semi-Supervised Learning with Deep Generative Models
Diederik P. Kingma
Danilo Jimenez Rezende
S. Mohamed
Max Welling
GAN
SSL
BDL
80
2,731
0
20 Jun 2014
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
393
16,962
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
196
12,384
0
24 Jun 2012
1