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Wasserstein Auto-Encoders

Wasserstein Auto-Encoders

5 November 2017
Ilya O. Tolstikhin
Olivier Bousquet
Sylvain Gelly
B. Schölkopf
    DRL
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Papers citing "Wasserstein Auto-Encoders"

38 / 188 papers shown
Title
Defense Against Adversarial Attacks Using Feature Scattering-based
  Adversarial Training
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training
Haichao Zhang
Jianyu Wang
AAML
23
230
0
24 Jul 2019
A gradual, semi-discrete approach to generative network training via
  explicit Wasserstein minimization
A gradual, semi-discrete approach to generative network training via explicit Wasserstein minimization
Yucheng Chen
Matus Telgarsky
Chao Zhang
Bolton Bailey
Daniel J. Hsu
Jian-wei Peng
GAN
OT
16
17
0
08 Jun 2019
Style Generator Inversion for Image Enhancement and Animation
Style Generator Inversion for Image Enhancement and Animation
Aviv Gabbay
Yedid Hoshen
11
17
0
05 Jun 2019
Educating Text Autoencoders: Latent Representation Guidance via
  Denoising
Educating Text Autoencoders: Latent Representation Guidance via Denoising
T. Shen
Jonas W. Mueller
Regina Barzilay
Tommi Jaakkola
14
4
0
29 May 2019
Fast Algorithms for Computational Optimal Transport and Wasserstein
  Barycenter
Fast Algorithms for Computational Optimal Transport and Wasserstein Barycenter
Wenshuo Guo
Nhat Ho
Michael I. Jordan
OT
17
5
0
23 May 2019
Toward Learning a Unified Many-to-Many Mapping for Diverse Image
  Translation
Toward Learning a Unified Many-to-Many Mapping for Diverse Image Translation
Wenju Xu
Shawn Keshmiri
Guanghui Wang
GAN
33
53
0
21 May 2019
Sliced Score Matching: A Scalable Approach to Density and Score
  Estimation
Sliced Score Matching: A Scalable Approach to Density and Score Estimation
Yang Song
Sahaj Garg
Jiaxin Shi
Stefano Ermon
31
398
0
17 May 2019
Kernel Mean Matching for Content Addressability of GANs
Kernel Mean Matching for Content Addressability of GANs
Wittawat Jitkrittum
Patsorn Sangkloy
Muhammad Waleed Gondal
Amit Raj
James Hays
Bernhard Schölkopf
GAN
BDL
24
9
0
14 May 2019
The Level Weighted Structural Similarity Loss: A Step Away from the MSE
The Level Weighted Structural Similarity Loss: A Step Away from the MSE
Yingjing Lu
17
27
0
30 Apr 2019
Effective Estimation of Deep Generative Language Models
Effective Estimation of Deep Generative Language Models
Tom Pelsmaeker
Wilker Aziz
BDL
22
27
0
17 Apr 2019
Assisted Sound Sample Generation with Musical Conditioning in
  Adversarial Auto-Encoders
Assisted Sound Sample Generation with Musical Conditioning in Adversarial Auto-Encoders
Adrien Bitton
P. Esling
Antoine Caillon
Martin Fouilleul
28
10
0
12 Apr 2019
Towards Photographic Image Manipulation with Balanced Growing of
  Generative Autoencoders
Towards Photographic Image Manipulation with Balanced Growing of Generative Autoencoders
Ari Heljakka
Arno Solin
Arno Solin
DRL
CVBM
27
15
0
12 Apr 2019
Sliced Wasserstein Generative Models
Jiqing Wu
Zhiwu Huang
Dinesh Acharya
Wen Li
Janine Thoma
D. Paudel
Luc Van Gool
DiffM
22
124
0
10 Apr 2019
Learning Implicit Generative Models by Matching Perceptual Features
Learning Implicit Generative Models by Matching Perceptual Features
Cicero Nogueira dos Santos
Youssef Mroueh
Inkit Padhi
Pierre L. Dognin
GAN
23
28
0
04 Apr 2019
Variational Adversarial Active Learning
Variational Adversarial Active Learning
Samarth Sinha
Sayna Ebrahimi
Trevor Darrell
GAN
DRL
VLM
SSL
33
570
0
31 Mar 2019
From Variational to Deterministic Autoencoders
From Variational to Deterministic Autoencoders
Partha Ghosh
Mehdi S. M. Sajjadi
Antonio Vergari
Michael J. Black
Bernhard Schölkopf
DRL
17
269
0
29 Mar 2019
Hypernetwork functional image representation
Hypernetwork functional image representation
Sylwester Klocek
Lukasz Maziarka
Maciej Wołczyk
Jacek Tabor
Jakub Nowak
Marek Śmieja
SupR
3DH
16
90
0
27 Feb 2019
LOSSGRAD: automatic learning rate in gradient descent
LOSSGRAD: automatic learning rate in gradient descent
B. Wójcik
Lukasz Maziarka
Jacek Tabor
ODL
32
4
0
20 Feb 2019
2-Wasserstein Approximation via Restricted Convex Potentials with
  Application to Improved Training for GANs
2-Wasserstein Approximation via Restricted Convex Potentials with Application to Improved Training for GANs
Amirhossein Taghvaei
Amin Jalali
33
42
0
19 Feb 2019
(q,p)-Wasserstein GANs: Comparing Ground Metrics for Wasserstein GANs
(q,p)-Wasserstein GANs: Comparing Ground Metrics for Wasserstein GANs
Anton Mallasto
J. Frellsen
Wouter Boomsma
Aasa Feragen
14
15
0
10 Feb 2019
Deep Generative Learning via Variational Gradient Flow
Deep Generative Learning via Variational Gradient Flow
Yuan Gao
Yuling Jiao
Yang Wang
Yao Wang
Can Yang
Shunkang Zhang
19
36
0
24 Jan 2019
Continuous Hierarchical Representations with Poincaré Variational
  Auto-Encoders
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders
Emile Mathieu
Charline Le Lan
Chris J. Maddison
Ryota Tomioka
Yee Whye Teh
BDL
DRL
26
171
0
17 Jan 2019
Lagging Inference Networks and Posterior Collapse in Variational
  Autoencoders
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders
Junxian He
Daniel M. Spokoyny
Graham Neubig
Taylor Berg-Kirkpatrick
BDL
DRL
14
272
0
16 Jan 2019
Conditional deep surrogate models for stochastic, high-dimensional, and
  multi-fidelity systems
Conditional deep surrogate models for stochastic, high-dimensional, and multi-fidelity systems
Yibo Yang
P. Perdikaris
SyDa
BDL
AI4CE
21
55
0
15 Jan 2019
Spread Divergence
Spread Divergence
Mingtian Zhang
Peter Hayes
Thomas Bird
Raza Habib
David Barber
MedIm
UD
30
20
0
21 Nov 2018
Sparsemax and Relaxed Wasserstein for Topic Sparsity
Sparsemax and Relaxed Wasserstein for Topic Sparsity
Tianyi Lin
Z. Hu
Xin Guo
14
37
0
22 Oct 2018
Entropic GANs meet VAEs: A Statistical Approach to Compute Sample
  Likelihoods in GANs
Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs
Yogesh Balaji
Hamed Hassani
Rama Chellappa
S. Feizi
GAN
DRL
41
20
0
09 Oct 2018
DT-LET: Deep Transfer Learning by Exploring where to Transfer
DT-LET: Deep Transfer Learning by Exploring where to Transfer
Jianzhe Lin
Qi. Wang
Rabab Ward
Z. J. Wang
11
27
0
23 Sep 2018
Variational Autoencoder with Implicit Optimal Priors
Variational Autoencoder with Implicit Optimal Priors
Hiroshi Takahashi
Tomoharu Iwata
Yuki Yamanaka
Masanori Yamada
Satoshi Yagi
DRL
26
61
0
14 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
18
482
0
14 Aug 2018
Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation
Stochastic Wasserstein Autoencoder for Probabilistic Sentence Generation
Hareesh Bahuleyan
Lili Mou
Hao Zhou
Olga Vechtomova
BDL
DRL
19
6
0
22 Jun 2018
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal
  Transport and Diffusions
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions
Antoine Liutkus
Umut Simsekli
Szymon Majewski
Alain Durmus
Fabian-Robert Stöter
DiffM
32
119
0
21 Jun 2018
Learning Factorized Multimodal Representations
Learning Factorized Multimodal Representations
Yao-Hung Hubert Tsai
Paul Pu Liang
Amir Zadeh
Louis-Philippe Morency
Ruslan Salakhutdinov
DRL
61
402
0
16 Jun 2018
DialogWAE: Multimodal Response Generation with Conditional Wasserstein
  Auto-Encoder
DialogWAE: Multimodal Response Generation with Conditional Wasserstein Auto-Encoder
Xiaodong Gu
Kyunghyun Cho
Jung-Woo Ha
Sunghun Kim
DRL
33
129
0
31 May 2018
On representation power of neural network-based graph embedding and
  beyond
On representation power of neural network-based graph embedding and beyond
Akifumi Okuno
Hidetoshi Shimodaira
9
2
0
31 May 2018
Wasserstein Variational Inference
Wasserstein Variational Inference
L. Ambrogioni
Umut Güçlü
Yağmur Güçlütürk
Max Hinne
E. Maris
Marcel van Gerven
BDL
DRL
11
42
0
29 May 2018
Deep Generative Models for Distribution-Preserving Lossy Compression
Deep Generative Models for Distribution-Preserving Lossy Compression
Michael Tschannen
E. Agustsson
Mario Lucic
14
130
0
28 May 2018
Generating Natural Adversarial Examples
Generating Natural Adversarial Examples
Zhengli Zhao
Dheeru Dua
Sameer Singh
GAN
AAML
38
596
0
31 Oct 2017
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