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Exploiting Chain Rule and Bayes' Theorem to Compare Probability
  Distributions

Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions

28 December 2020
Huangjie Zheng
Mingyuan Zhou
    OT
ArXivPDFHTML

Papers citing "Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions"

50 / 54 papers shown
Title
Leveraging Segment Anything Model for Source-Free Domain Adaptation via Dual Feature Guided Auto-Prompting
Leveraging Segment Anything Model for Source-Free Domain Adaptation via Dual Feature Guided Auto-Prompting
Zheang Huai
Hui Tang
Yi Li
Zhe Chen
Xiaomeng Li
VLM
117
0
0
13 May 2025
TsCA: On the Semantic Consistency Alignment via Conditional Transport for Compositional Zero-Shot Learning
TsCA: On the Semantic Consistency Alignment via Conditional Transport for Compositional Zero-Shot Learning
Miaoge Li
Jingcai Guo
Richard Yi Da Xu
Dongsheng Wang
Xiaofeng Cao
Zhijie Rao
Song Guo
CoGe
123
3
0
28 Jan 2025
Partition-Guided GANs
Partition-Guided GANs
Mohammadreza Armandpour
A. Sadeghian
Chunyuan Li
Mingyuan Zhou
GAN
47
19
0
02 Apr 2021
Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein
  Distance)
Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein Distance)
Jan Stanczuk
Christian Etmann
L. Kreusser
Carola-Bibiane Schönlieb
GAN
28
48
0
02 Mar 2021
Score-Based Generative Modeling through Stochastic Differential
  Equations
Score-Based Generative Modeling through Stochastic Differential Equations
Yang Song
Jascha Narain Sohl-Dickstein
Diederik P. Kingma
Abhishek Kumar
Stefano Ermon
Ben Poole
DiffM
SyDa
264
6,293
0
26 Nov 2020
Differentiable Augmentation for Data-Efficient GAN Training
Differentiable Augmentation for Data-Efficient GAN Training
Shengyu Zhao
Zhijian Liu
Ji Lin
Jun-Yan Zhu
Song Han
74
603
0
18 Jun 2020
Training Generative Adversarial Networks with Limited Data
Training Generative Adversarial Networks with Limited Data
Tero Karras
M. Aittala
Janne Hellsten
S. Laine
J. Lehtinen
Timo Aila
GAN
118
1,873
0
11 Jun 2020
Image Augmentations for GAN Training
Image Augmentations for GAN Training
Zhengli Zhao
Zizhao Zhang
Ting-Li Chen
Sameer Singh
Han Zhang
51
137
0
04 Jun 2020
Analyzing and Improving the Image Quality of StyleGAN
Analyzing and Improving the Image Quality of StyleGAN
Tero Karras
S. Laine
M. Aittala
Janne Hellsten
J. Lehtinen
Timo Aila
GAN
256
5,769
0
03 Dec 2019
Prescribed Generative Adversarial Networks
Prescribed Generative Adversarial Networks
Adji Bousso Dieng
Francisco J. R. Ruiz
David M. Blei
Michalis K. Titsias
GAN
DRL
46
61
0
09 Oct 2019
How Well Do WGANs Estimate the Wasserstein Metric?
How Well Do WGANs Estimate the Wasserstein Metric?
Anton Mallasto
Guido Montúfar
Augusto Gerolin
32
25
0
09 Oct 2019
On the estimation of the Wasserstein distance in generative models
On the estimation of the Wasserstein distance in generative models
Thomas Pinetz
Daniel Soukup
Thomas Pock
GAN
39
9
0
02 Oct 2019
MaskGAN: Towards Diverse and Interactive Facial Image Manipulation
MaskGAN: Towards Diverse and Interactive Facial Image Manipulation
Cheng-Han Lee
Ziwei Liu
Lingyun Wu
Ping Luo
CVBM
134
1,070
0
27 Jul 2019
Large Scale Adversarial Representation Learning
Large Scale Adversarial Representation Learning
Jeff Donahue
Karen Simonyan
SSL
101
542
0
04 Jul 2019
Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling
Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling
Hao Zhang
Bo Chen
Long Tian
Zhengjue Wang
Mingyuan Zhou
DRL
43
7
0
18 May 2019
Sliced Wasserstein Generative Models
Jiqing Wu
Zhiwu Huang
Dinesh Acharya
Wen Li
Janine Thoma
D. Paudel
Luc Van Gool
DiffM
113
126
0
10 Apr 2019
Generalized Sliced Wasserstein Distances
Generalized Sliced Wasserstein Distances
Soheil Kolouri
Kimia Nadjahi
Umut Simsekli
Roland Badeau
Gustavo K. Rohde
30
296
0
01 Feb 2019
A Style-Based Generator Architecture for Generative Adversarial Networks
A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras
S. Laine
Timo Aila
504
10,500
0
12 Dec 2018
Self-Supervised GANs via Auxiliary Rotation Loss
Self-Supervised GANs via Auxiliary Rotation Loss
Ting Chen
Xiaohua Zhai
Marvin Ritter
Mario Lucic
N. Houlsby
SSL
GAN
60
302
0
27 Nov 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
Soheil Feizi
GAN
DRL
48
20
0
09 Oct 2018
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Andrew Brock
Jeff Donahue
Karen Simonyan
218
5,363
0
28 Sep 2018
Understanding VAEs in Fisher-Shannon Plane
Understanding VAEs in Fisher-Shannon Plane
Huangjie Zheng
Jiangchao Yao
Ya Zhang
Ivor W. Tsang
Jia Wang
34
12
0
10 Jul 2018
Semi-Implicit Variational Inference
Semi-Implicit Variational Inference
Mingzhang Yin
Mingyuan Zhou
BDL
64
126
0
28 May 2018
Self-Attention Generative Adversarial Networks
Self-Attention Generative Adversarial Networks
Han Zhang
Ian Goodfellow
Dimitris N. Metaxas
Augustus Odena
GAN
111
3,710
0
21 May 2018
Generative Modeling using the Sliced Wasserstein Distance
Generative Modeling using the Sliced Wasserstein Distance
Ishani Deshpande
Ziyu Zhang
Alex Schwing
GAN
41
223
0
29 Mar 2018
Improving GANs Using Optimal Transport
Improving GANs Using Optimal Transport
Tim Salimans
Han Zhang
Alec Radford
Dimitris N. Metaxas
OT
GAN
47
323
0
15 Mar 2018
Computational Optimal Transport
Computational Optimal Transport
Gabriel Peyré
Marco Cuturi
OT
138
2,133
0
01 Mar 2018
Degeneration in VAE: in the Light of Fisher Information Loss
Degeneration in VAE: in the Light of Fisher Information Loss
Huangjie Zheng
Jiangchao Yao
Ya Zhang
Ivor W. Tsang
DRL
37
17
0
19 Feb 2018
Spectral Normalization for Generative Adversarial Networks
Spectral Normalization for Generative Adversarial Networks
Takeru Miyato
Toshiki Kataoka
Masanori Koyama
Yuichi Yoshida
ODL
135
4,421
0
16 Feb 2018
Demystifying MMD GANs
Demystifying MMD GANs
Mikolaj Binkowski
Danica J. Sutherland
Michael Arbel
Arthur Gretton
EGVM
88
1,478
0
04 Jan 2018
Geometrical Insights for Implicit Generative Modeling
Geometrical Insights for Implicit Generative Modeling
Léon Bottou
Martín Arjovsky
David Lopez-Paz
Maxime Oquab
43
49
0
21 Dec 2017
PacGAN: The power of two samples in generative adversarial networks
PacGAN: The power of two samples in generative adversarial networks
Zinan Lin
A. Khetan
Giulia Fanti
Sewoong Oh
GAN
52
333
0
12 Dec 2017
Progressive Growing of GANs for Improved Quality, Stability, and
  Variation
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Tero Karras
Timo Aila
S. Laine
J. Lehtinen
GAN
100
7,318
0
27 Oct 2017
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At
  Every Step
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step
W. Fedus
Mihaela Rosca
Balaji Lakshminarayanan
Andrew M. Dai
S. Mohamed
Ian Goodfellow
GAN
49
210
0
23 Oct 2017
InfoVAE: Information Maximizing Variational Autoencoders
InfoVAE: Information Maximizing Variational Autoencoders
Shengjia Zhao
Jiaming Song
Stefano Ermon
DRL
69
442
0
07 Jun 2017
Learning Generative Models with Sinkhorn Divergences
Learning Generative Models with Sinkhorn Divergences
Aude Genevay
Gabriel Peyré
Marco Cuturi
OT
114
625
0
01 Jun 2017
The Cramer Distance as a Solution to Biased Wasserstein Gradients
The Cramer Distance as a Solution to Biased Wasserstein Gradients
Marc G. Bellemare
Ivo Danihelka
Will Dabney
S. Mohamed
Balaji Lakshminarayanan
Stephan Hoyer
Rémi Munos
GAN
42
344
0
30 May 2017
MMD GAN: Towards Deeper Understanding of Moment Matching Network
MMD GAN: Towards Deeper Understanding of Moment Matching Network
Chun-Liang Li
Wei-Cheng Chang
Yu Cheng
Yiming Yang
Barnabás Póczós
GAN
50
720
0
24 May 2017
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational
  Learning
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
Akash Srivastava
Lazar Valkov
Chris Russell
Michael U. Gutmann
Charles Sutton
SyDa
GAN
48
677
0
22 May 2017
Improved Training of Wasserstein GANs
Improved Training of Wasserstein GANs
Ishaan Gulrajani
Faruk Ahmed
Martín Arjovsky
Vincent Dumoulin
Aaron Courville
GAN
130
9,509
0
31 Mar 2017
Variational Inference using Implicit Distributions
Variational Inference using Implicit Distributions
Ferenc Huszár
DRL
GAN
105
135
0
27 Feb 2017
Variational Lossy Autoencoder
Variational Lossy Autoencoder
Xi Chen
Diederik P. Kingma
Tim Salimans
Yan Duan
Prafulla Dhariwal
John Schulman
Ilya Sutskever
Pieter Abbeel
DRL
SSL
GAN
109
674
0
08 Nov 2016
Learning in Implicit Generative Models
Learning in Implicit Generative Models
S. Mohamed
Balaji Lakshminarayanan
GAN
118
415
0
11 Oct 2016
Improved Techniques for Training GANs
Improved Techniques for Training GANs
Tim Salimans
Ian Goodfellow
Wojciech Zaremba
Vicki Cheung
Alec Radford
Xi Chen
GAN
368
8,999
0
10 Jun 2016
Variational Inference: A Review for Statisticians
Variational Inference: A Review for Statisticians
David M. Blei
A. Kucukelbir
Jon D. McAuliffe
BDL
181
4,748
0
04 Jan 2016
Rethinking the Inception Architecture for Computer Vision
Rethinking the Inception Architecture for Computer Vision
Christian Szegedy
Vincent Vanhoucke
Sergey Ioffe
Jonathon Shlens
Z. Wojna
3DV
BDL
478
27,231
0
02 Dec 2015
Unsupervised Representation Learning with Deep Convolutional Generative
  Adversarial Networks
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Alec Radford
Luke Metz
Soumith Chintala
GAN
OOD
232
13,968
0
19 Nov 2015
LSUN: Construction of a Large-scale Image Dataset using Deep Learning
  with Humans in the Loop
LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop
Feng Yu
Ari Seff
Yinda Zhang
Shuran Song
Thomas Funkhouser
Jianxiong Xiao
49
2,320
0
10 Jun 2015
Generative Moment Matching Networks
Generative Moment Matching Networks
Yujia Li
Kevin Swersky
R. Zemel
OOD
GAN
90
844
0
10 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
808
149,474
0
22 Dec 2014
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