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Learning Disentangled Representations with Semi-Supervised Deep
  Generative Models

Learning Disentangled Representations with Semi-Supervised Deep Generative Models

1 June 2017
Siddharth Narayanaswamy
Brooks Paige
Jan-Willem van de Meent
Alban Desmaison
Noah D. Goodman
Pushmeet Kohli
Frank Wood
Philip Torr
    DRL
    CoGe
ArXivPDFHTML

Papers citing "Learning Disentangled Representations with Semi-Supervised Deep Generative Models"

27 / 77 papers shown
Title
Theory and Evaluation Metrics for Learning Disentangled Representations
Theory and Evaluation Metrics for Learning Disentangled Representations
Kien Do
T. Tran
CoGe
DRL
18
93
0
26 Aug 2019
Y-Autoencoders: disentangling latent representations via
  sequential-encoding
Y-Autoencoders: disentangling latent representations via sequential-encoding
Massimiliano Patacchiola
P. Fox-Roberts
E. Rosten
OOD
DRL
21
13
0
25 Jul 2019
On the Transfer of Inductive Bias from Simulation to the Real World: a
  New Disentanglement Dataset
On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset
Muhammad Waleed Gondal
Manuel Wüthrich
Ðorðe Miladinovic
Francesco Locatello
M. Breidt
V. Volchkov
J. Akpo
Olivier Bachem
Bernhard Schölkopf
Stefan Bauer
OOD
DRL
33
134
0
07 Jun 2019
DIVA: Domain Invariant Variational Autoencoders
DIVA: Domain Invariant Variational Autoencoders
Maximilian Ilse
Jakub M. Tomczak
Christos Louizos
Max Welling
DRL
OOD
33
198
0
24 May 2019
Flat Metric Minimization with Applications in Generative Modeling
Flat Metric Minimization with Applications in Generative Modeling
Thomas Möllenhoff
Daniel Cremers
17
5
0
12 May 2019
Adversarial Variational Embedding for Robust Semi-supervised Learning
Adversarial Variational Embedding for Robust Semi-supervised Learning
Xiang Zhang
Lina Yao
Feng Yuan
DRL
GAN
30
42
0
07 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
34
123
0
03 May 2019
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data
Pierre-Alexandre Mattei
J. Frellsen
SyDa
25
45
0
06 Dec 2018
Rare Event Detection using Disentangled Representation Learning
Rare Event Detection using Disentangled Representation Learning
Ryuhei Hamaguchi
Ken Sakurada
Ryosuke Nakamura
DRL
20
35
0
04 Dec 2018
Disentangling Latent Hands for Image Synthesis and Pose Estimation
Disentangling Latent Hands for Image Synthesis and Pose Estimation
Linlin Yang
Angela Yao
CoGe
DRL
28
116
0
03 Dec 2018
Robustly Disentangled Causal Mechanisms: Validating Deep Representations
  for Interventional Robustness
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness
Raphael Suter
Ðorðe Miladinovic
Bernhard Schölkopf
Stefan Bauer
CML
OOD
DRL
19
159
0
31 Oct 2018
Pyro: Deep Universal Probabilistic Programming
Pyro: Deep Universal Probabilistic Programming
Eli Bingham
Jonathan P. Chen
M. Jankowiak
F. Obermeyer
Neeraj Pradhan
Theofanis Karaletsos
Rohit Singh
Paul A. Szerlip
Paul Horsfall
Noah D. Goodman
BDL
GP
72
1,030
0
18 Oct 2018
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language
  Understanding
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding
Kexin Yi
Jiajun Wu
Chuang Gan
Antonio Torralba
Pushmeet Kohli
J. Tenenbaum
NAI
46
599
0
04 Oct 2018
Hyperprior Induced Unsupervised Disentanglement of Latent
  Representations
Hyperprior Induced Unsupervised Disentanglement of Latent Representations
Abdul Fatir Ansari
Harold Soh
CoGe
CML
UD
DRL
26
31
0
12 Sep 2018
Analyzing Inverse Problems with Invertible Neural Networks
Analyzing Inverse Problems with Invertible Neural Networks
Lynton Ardizzone
Jakob Kruse
Sebastian J. Wirkert
D. Rahner
E. Pellegrini
R. Klessen
Lena Maier-Hein
Carsten Rother
Ullrich Kothe
21
483
0
14 Aug 2018
Efficient Probabilistic Inference in the Quest for Physics Beyond the
  Standard Model
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
A. G. Baydin
Lukas Heinrich
W. Bhimji
Lei Shao
Saeid Naderiparizi
...
Philip Torr
Victor W. Lee
P. Prabhat
Kyle Cranmer
Frank Wood
29
31
0
20 Jul 2018
Mining gold from implicit models to improve likelihood-free inference
Mining gold from implicit models to improve likelihood-free inference
Johann Brehmer
Gilles Louppe
J. Pavez
Kyle Cranmer
AI4CE
TPM
38
181
0
30 May 2018
Meta-Learning Probabilistic Inference For Prediction
Meta-Learning Probabilistic Inference For Prediction
Jonathan Gordon
J. Bronskill
Matthias Bauer
Sebastian Nowozin
Richard Turner
BDL
45
263
0
24 May 2018
Disentangling Controllable and Uncontrollable Factors of Variation by
  Interacting with the World
Disentangling Controllable and Uncontrollable Factors of Variation by Interacting with the World
Yoshihide Sawada
DRL
21
10
0
19 Apr 2018
Structured Disentangled Representations
Structured Disentangled Representations
Babak Esmaeili
Hao Wu
Sarthak Jain
Alican Bozkurt
N. Siddharth
Brooks Paige
Dana H. Brooks
Jennifer Dy
Jan-Willem van de Meent
OOD
CML
BDL
DRL
33
165
0
06 Apr 2018
Factorised spatial representation learning: application in
  semi-supervised myocardial segmentation
Factorised spatial representation learning: application in semi-supervised myocardial segmentation
A. Chartsias
T. Joyce
G. Papanastasiou
S. Semple
M. Williams
D. Newby
R. Dharmakumar
Sotirios A. Tsaftaris
DRL
51
69
0
19 Mar 2018
Disentangling by Factorising
Disentangling by Factorising
Hyunjik Kim
A. Mnih
CoGe
OOD
12
1,327
0
16 Feb 2018
Multi-Objective De Novo Drug Design with Conditional Graph Generative
  Model
Multi-Objective De Novo Drug Design with Conditional Graph Generative Model
Yibo Li
L. Zhang
Zhenming Liu
43
335
0
18 Jan 2018
Learning to Write Stylized Chinese Characters by Reading a Handful of
  Examples
Learning to Write Stylized Chinese Characters by Reading a Handful of Examples
D. Sun
Tongzheng Ren
Chongxun Li
Hang Su
Jun Zhu
29
87
0
06 Dec 2017
Guiding InfoGAN with Semi-Supervision
Guiding InfoGAN with Semi-Supervision
Adrian Spurr
Emre Aksan
Otmar Hilliges
GAN
34
46
0
14 Jul 2017
Toward Controlled Generation of Text
Toward Controlled Generation of Text
Zhiting Hu
Zichao Yang
Xiaodan Liang
Ruslan Salakhutdinov
Eric Xing
61
984
0
02 Mar 2017
Automatic differentiation in machine learning: a survey
Automatic differentiation in machine learning: a survey
A. G. Baydin
Barak A. Pearlmutter
Alexey Radul
J. Siskind
PINN
AI4CE
ODL
75
2,750
0
20 Feb 2015
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