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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"

50 / 188 papers shown
Title
Deep Generative Modelling: A Comparative Review of VAEs, GANs,
  Normalizing Flows, Energy-Based and Autoregressive Models
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models
Sam Bond-Taylor
Adam Leach
Yang Long
Chris G. Willcocks
VLM
TPM
41
480
0
08 Mar 2021
Generalizing to Unseen Domains: A Survey on Domain Generalization
Generalizing to Unseen Domains: A Survey on Domain Generalization
Jindong Wang
Cuiling Lan
Chang-Shu Liu
Yidong Ouyang
Tao Qin
Wang Lu
Yiqiang Chen
Wenjun Zeng
Philip S. Yu
OOD
54
1,170
0
02 Mar 2021
Neuron Coverage-Guided Domain Generalization
Neuron Coverage-Guided Domain Generalization
Chris Xing Tian
Haoliang Li
Xiaofei Xie
Yang Liu
Shiqi Wang
23
35
0
27 Feb 2021
Spatio-Temporal Graph Dual-Attention Network for Multi-Agent Prediction
  and Tracking
Spatio-Temporal Graph Dual-Attention Network for Multi-Agent Prediction and Tracking
Jiachen Li
Hengbo Ma
Zhihao Zhang
Jinning Li
M. Tomizuka
55
68
0
18 Feb 2021
On Robust Optimal Transport: Computational Complexity and Barycenter
  Computation
On Robust Optimal Transport: Computational Complexity and Barycenter Computation
Khang Le
Huy Le Nguyen
Quang H. Nguyen
Tung Pham
Hung Bui
Nhat Ho
OT
28
37
0
13 Feb 2021
Learning Audio-Visual Correlations from Variational Cross-Modal
  Generation
Learning Audio-Visual Correlations from Variational Cross-Modal Generation
Ye Zhu
Yu Wu
Hugo Latapie
Yi Yang
Yan Yan
SSL
16
20
0
05 Feb 2021
Smooth $p$-Wasserstein Distance: Structure, Empirical Approximation, and
  Statistical Applications
Smooth ppp-Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications
Sloan Nietert
Ziv Goldfeld
Kengo Kato
34
30
0
11 Jan 2021
Probabilistic Outlier Detection and Generation
Probabilistic Outlier Detection and Generation
S. Rizzo
L. Pang
Yixian Chen
S. Chawla
13
0
0
22 Dec 2020
Making transport more robust and interpretable by moving data through a
  small number of anchor points
Making transport more robust and interpretable by moving data through a small number of anchor points
Chi-Heng Lin
Mehdi Azabou
Eva L. Dyer
OT
OOD
27
22
0
21 Dec 2020
Barking up the right tree: an approach to search over molecule synthesis
  DAGs
Barking up the right tree: an approach to search over molecule synthesis DAGs
John Bradshaw
Brooks Paige
Matt J. Kusner
Marwin H. S. Segler
José Miguel Hernández-Lobato
51
56
0
21 Dec 2020
A case for new neural network smoothness constraints
A case for new neural network smoothness constraints
Mihaela Rosca
T. Weber
A. Gretton
S. Mohamed
AAML
30
48
0
14 Dec 2020
Generative Capacity of Probabilistic Protein Sequence Models
Generative Capacity of Probabilistic Protein Sequence Models
Francisco McGee
Quentin Novinger
R. Levy
Vincenzo Carnevale
A. Haldane
27
34
0
03 Dec 2020
TAN-NTM: Topic Attention Networks for Neural Topic Modeling
TAN-NTM: Topic Attention Networks for Neural Topic Modeling
Madhur Panwar
Shashank Shailabh
Milan Aggarwal
Balaji Krishnamurthy
15
24
0
02 Dec 2020
Optimizing Molecules using Efficient Queries from Property Evaluations
Optimizing Molecules using Efficient Queries from Property Evaluations
Samuel C. Hoffman
Vijil Chenthamarakshan
Kahini Wadhawan
Pin-Yu Chen
Payel Das
37
68
0
03 Nov 2020
Neural Topic Modeling by Incorporating Document Relationship Graph
Neural Topic Modeling by Incorporating Document Relationship Graph
Deyu Zhou
Xuemeng Hu
Rui Wang
14
22
0
29 Sep 2020
Generative Model without Prior Distribution Matching
Generative Model without Prior Distribution Matching
Cong Geng
Jia Wang
L. Chen
Zhiyong Gao
GAN
118
1
0
23 Sep 2020
Generative models with kernel distance in data space
Generative models with kernel distance in data space
Szymon Knop
Marcin Mazur
P. Spurek
Jacek Tabor
Igor T. Podolak
GAN
SyDa
19
11
0
15 Sep 2020
Adversarial score matching and improved sampling for image generation
Adversarial score matching and improved sampling for image generation
Alexia Jolicoeur-Martineau
Remi Piche-Taillefer
Rémi Tachet des Combes
Ioannis Mitliagkas
DiffM
24
125
0
11 Sep 2020
Generative Adversarial Networks for Image and Video Synthesis:
  Algorithms and Applications
Generative Adversarial Networks for Image and Video Synthesis: Algorithms and Applications
Xuan Li
Xun Huang
Jiahui Yu
Ting-Chun Wang
Arun Mallya
GAN
28
153
0
06 Aug 2020
Invertible Zero-Shot Recognition Flows
Invertible Zero-Shot Recognition Flows
Yuming Shen
Jie Qin
Lei Huang
BDL
AI4CE
19
99
0
09 Jul 2020
Efficient Learning of Generative Models via Finite-Difference Score
  Matching
Efficient Learning of Generative Models via Finite-Difference Score Matching
Tianyu Pang
Kun Xu
Chongxuan Li
Yang Song
Stefano Ermon
Jun Zhu
DiffM
31
53
0
07 Jul 2020
End-to-end Sinkhorn Autoencoder with Noise Generator
End-to-end Sinkhorn Autoencoder with Noise Generator
Kamil Deja
Jan Dubiñski
Piotr W. Nowak
S. Wenzel
Tomasz Trzciñski
SyDa
22
22
0
11 Jun 2020
Probabilistic Autoencoder
Probabilistic Autoencoder
Vanessa Böhm
U. Seljak
UQCV
BDL
DRL
16
32
0
09 Jun 2020
Nonparametric Score Estimators
Nonparametric Score Estimators
Yuhao Zhou
Jiaxin Shi
Jun Zhu
24
23
0
20 May 2020
Jigsaw-VAE: Towards Balancing Features in Variational Autoencoders
Jigsaw-VAE: Towards Balancing Features in Variational Autoencoders
Saeid Asgari Taghanaki
Mohammad Havaei
Alex Lamb
Aditya Sanghi
Aram Danielyan
Tonya Custis
DRL
25
7
0
12 May 2020
We Need to Talk About Random Splits
We Need to Talk About Random Splits
Anders Søgaard
Sebastian Ebert
Jasmijn Bastings
Katja Filippova
29
97
0
01 May 2020
A Batch Normalized Inference Network Keeps the KL Vanishing Away
A Batch Normalized Inference Network Keeps the KL Vanishing Away
Qile Zhu
Jianlin Su
Wei Bi
Xiaojiang Liu
Xiyao Ma
Xiaolin Li
D. Wu
BDL
DRL
34
61
0
27 Apr 2020
Learning to Learn Single Domain Generalization
Learning to Learn Single Domain Generalization
Fengchun Qiao
Long Zhao
Xi Peng
OOD
34
431
0
30 Mar 2020
Statistical and Topological Properties of Sliced Probability Divergences
Statistical and Topological Properties of Sliced Probability Divergences
Kimia Nadjahi
Alain Durmus
Lénaïc Chizat
Soheil Kolouri
Shahin Shahrampour
Umut Simsekli
26
80
0
12 Mar 2020
Deterministic Decoding for Discrete Data in Variational Autoencoders
Deterministic Decoding for Discrete Data in Variational Autoencoders
Daniil Polykovskiy
Dmitry Vetrov
OffRL
21
8
0
04 Mar 2020
Image Hashing by Minimizing Discrete Component-wise Wasserstein Distance
Image Hashing by Minimizing Discrete Component-wise Wasserstein Distance
Khoa D. Doan
Saurav Manchanda
Amir Kimiyaie
Chandan K. Reddy
6
5
0
29 Feb 2020
DP-MERF: Differentially Private Mean Embeddings with Random Features for
  Practical Privacy-Preserving Data Generation
DP-MERF: Differentially Private Mean Embeddings with Random Features for Practical Privacy-Preserving Data Generation
Frederik Harder
Kamil Adamczewski
Mijung Park
SyDa
25
101
0
26 Feb 2020
Balancing reconstruction error and Kullback-Leibler divergence in
  Variational Autoencoders
Balancing reconstruction error and Kullback-Leibler divergence in Variational Autoencoders
Andrea Asperti
Matteo Trentin
DRL
22
96
0
18 Feb 2020
Towards GAN Benchmarks Which Require Generalization
Towards GAN Benchmarks Which Require Generalization
Ishaan Gulrajani
Colin Raffel
Luke Metz
24
57
0
10 Jan 2020
A Gentle Introduction to Deep Learning for Graphs
A Gentle Introduction to Deep Learning for Graphs
D. Bacciu
Federico Errica
A. Micheli
Marco Podda
AI4CE
GNN
42
276
0
29 Dec 2019
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal
  and Image Processing
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing
V. Monga
Yuelong Li
Yonina C. Eldar
31
997
0
22 Dec 2019
Deep Automodulators
Deep Automodulators
Ari Heljakka
Wenshuai Zhao
Arno Solin
Arno Solin
31
5
0
21 Dec 2019
Learning Weighted Submanifolds with Variational Autoencoders and
  Riemannian Variational Autoencoders
Learning Weighted Submanifolds with Variational Autoencoders and Riemannian Variational Autoencoders
Nina Miolane
S. Holmes
DRL
6
20
0
19 Nov 2019
Effectively Unbiased FID and Inception Score and where to find them
Effectively Unbiased FID and Inception Score and where to find them
Min Jin Chong
David A. Forsyth
EGVM
13
199
0
16 Nov 2019
Pre-train and Plug-in: Flexible Conditional Text Generation with
  Variational Auto-Encoders
Pre-train and Plug-in: Flexible Conditional Text Generation with Variational Auto-Encoders
Yu Duan
Canwen Xu
Jiaxin Pei
Jialong Han
Chenliang Li
16
42
0
10 Nov 2019
Uncertainty Quantification with Generative Models
Uncertainty Quantification with Generative Models
Vanessa Böhm
F. Lanusse
U. Seljak
14
25
0
22 Oct 2019
Bridging the Gap Between $f$-GANs and Wasserstein GANs
Bridging the Gap Between fff-GANs and Wasserstein GANs
Jiaming Song
Stefano Ermon
8
39
0
22 Oct 2019
Learning Model-Agnostic Counterfactual Explanations for Tabular Data
Learning Model-Agnostic Counterfactual Explanations for Tabular Data
Martin Pawelczyk
Johannes Haug
Klaus Broelemann
Gjergji Kasneci
OOD
CML
30
199
0
21 Oct 2019
Optimal Transport Based Generative Autoencoders
Optimal Transport Based Generative Autoencoders
Oliver Zhang
Ruei-Sung Lin
Yuchuan Gou
GAN
DRL
19
2
0
16 Oct 2019
DDTCDR: Deep Dual Transfer Cross Domain Recommendation
DDTCDR: Deep Dual Transfer Cross Domain Recommendation
P. Li
Alexander Tuzhilin
14
262
0
11 Oct 2019
Prescribed Generative Adversarial Networks
Prescribed Generative Adversarial Networks
Adji Bousso Dieng
Francisco J. R. Ruiz
David M. Blei
Michalis K. Titsias
GAN
DRL
21
61
0
09 Oct 2019
Adversarial Deep Embedded Clustering: on a better trade-off between
  Feature Randomness and Feature Drift
Adversarial Deep Embedded Clustering: on a better trade-off between Feature Randomness and Feature Drift
Nairouz Mrabah
Mohamed Bouguessa
Riadh Ksantini
OOD
14
53
0
26 Sep 2019
Balancing Reconstruction Quality and Regularisation in ELBO for VAEs
Balancing Reconstruction Quality and Regularisation in ELBO for VAEs
Shuyu Lin
Stephen J. Roberts
Niki Trigoni
R. Clark
DRL
18
15
0
09 Sep 2019
Conditional Flow Variational Autoencoders for Structured Sequence
  Prediction
Conditional Flow Variational Autoencoders for Structured Sequence Prediction
Apratim Bhattacharyya
M. Hanselmann
Mario Fritz
Bernt Schiele
C. Straehle
BDL
DRL
AI4TS
24
83
0
24 Aug 2019
Improve variational autoEncoder with auxiliary softmax multiclassifier
Improve variational autoEncoder with auxiliary softmax multiclassifier
Yao Li
DRL
21
0
0
17 Aug 2019
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