Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1610.02920
Cited By
v1
v2 (latest)
Generative Adversarial Nets from a Density Ratio Estimation Perspective
10 October 2016
Masatoshi Uehara
Issei Sato
Masahiro Suzuki
Kotaro Nakayama
Y. Matsuo
GAN
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Generative Adversarial Nets from a Density Ratio Estimation Perspective"
50 / 88 papers shown
Discriminative classification with generative features: bridging Naive Bayes and logistic regression
Zachary Terner
Alexander Petersen
Yuedong Wang
25
0
0
30 Nov 2025
Zero-Shot Adaptation of Behavioral Foundation Models to Unseen Dynamics
Maksim Bobrin
Ilya Zisman
Alexander Nikulin
Vladislav Kurenkov
Dmitry V. Dylov
OffRL
222
2
0
19 May 2025
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models
Jialong Jiang
Wenkang Hu
Jian Huang
Yuling Jiao
Xu Liu
DiffM
260
0
0
08 May 2025
Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion
Ruixiang Zhang
Shuangfei Zhai
Yizhe Zhang
James Thornton
Zijing Ou
Joshua M. Susskind
Navdeep Jaitly
DiffM
260
17
0
23 Apr 2025
Improving Discriminator Guidance in Diffusion Models
Alexandre Verine
Mehdi Inane
Florian Le Bronnec
Benjamin Négrevergne
Y. Chevaleyre
DiffM
306
0
0
20 Mar 2025
Bounds on Lp errors in density ratio estimation via f-divergence loss functions
International Conference on Learning Representations (ICLR), 2024
Yoshiaki Kitazawa
280
2
0
02 Oct 2024
A density ratio framework for evaluating the utility of synthetic data
Thom Benjamin Volker
Peter-Paul de Wolf
E. V. Kesteren
193
0
0
23 Aug 2024
Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift
Neural Information Processing Systems (NeurIPS), 2024
Jiawei Ge
Debarghya Mukherjee
Jianqing Fan
266
4
0
16 May 2024
Training Unbiased Diffusion Models From Biased Dataset
Yeongmin Kim
Byeonghu Na
Minsang Park
Joonho Jang
Dongjun Kim
Wanmo Kang
Il-Chul Moon
290
32
0
02 Mar 2024
Insights into Closed-form IPM-GAN Discriminator Guidance for Diffusion Modeling
Aadithya Srikanth
Siddarth Asokan
Nishanth Shetty
C. Seelamantula
303
0
0
02 Jun 2023
Machine Learning and the Future of Bayesian Computation
Steven Winter
Trevor Campbell
Lizhen Lin
Sanvesh Srivastava
David B. Dunson
TPM
318
6
0
21 Apr 2023
MonoFlow: Rethinking Divergence GANs via the Perspective of Wasserstein Gradient Flows
International Conference on Machine Learning (ICML), 2023
Mingxuan Yi
Zhanxing Zhu
Song Liu
GAN
475
17
0
02 Feb 2023
Generalized Balancing Weights via Deep Neural Networks
Yoshiaki Kitazawa
BDL
CML
387
1
0
14 Nov 2022
Forget-me-not! Contrastive Critics for Mitigating Posterior Collapse
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Sachit Menon
David M. Blei
Carl Vondrick
DRL
303
8
0
19 Jul 2022
A General Recipe for Likelihood-free Bayesian Optimization
International Conference on Machine Learning (ICML), 2022
Jiaming Song
Lantao Yu
Willie Neiswanger
Stefano Ermon
256
28
0
27 Jun 2022
A Unified f-divergence Framework Generalizing VAE and GAN
Jaime Roquero Gimenez
James Zou
125
2
0
11 May 2022
Unified Perspective on Probability Divergence via Maximum Likelihood Density Ratio Estimation: Bridging KL-Divergence and Integral Probability Metrics
Masahiro Kato
Masaaki Imaizumi
Kentaro Minami
188
0
0
31 Jan 2022
A Unified Framework for Multi-distribution Density Ratio Estimation
Lantao Yu
Yujia Jin
Stefano Ermon
150
5
0
07 Dec 2021
F-Divergences and Cost Function Locality in Generative Modelling with Quantum Circuits
Chiara Leadbeater
Louis Sharrock
Brian Coyle
Marcello Benedetti
232
12
0
08 Oct 2021
Meta-Learning for Relative Density-Ratio Estimation
Atsutoshi Kumagai
Tomoharu Iwata
Yasuhiro Fujiwara
238
11
0
02 Jul 2021
Near-Optimal Linear Regression under Distribution Shift
International Conference on Machine Learning (ICML), 2021
Qi Lei
Wei Hu
Jason D. Lee
OOD
146
44
0
23 Jun 2021
Improving Bridge estimators via
f
f
f
-GAN
Statistics and computing (Stat Comput), 2021
Hanwen Xing
OT
296
4
0
14 Jun 2021
Continual Density Ratio Estimation in an Online Setting
Yu Chen
Song Liu
Tom Diethe
Peter A. Flach
154
2
0
09 Mar 2021
A Theory of Label Propagation for Subpopulation Shift
International Conference on Machine Learning (ICML), 2021
Tianle Cai
Ruiqi Gao
Jason D. Lee
Qi Lei
267
55
0
22 Feb 2021
3D Human motion anticipation and classification
Emad Barsoum
J. Kender
Zicheng Liu
3DH
127
2
0
31 Dec 2020
C-Learning: Learning to Achieve Goals via Recursive Classification
International Conference on Learning Representations (ICLR), 2020
Benjamin Eysenbach
Ruslan Salakhutdinov
Sergey Levine
OffRL
291
87
0
17 Nov 2020
Improving Maximum Likelihood Training for Text Generation with Density Ratio Estimation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Yuxuan Song
Ning Miao
Hao Zhou
Lantao Yu
Mingxuan Wang
Lei Li
166
7
0
12 Jul 2020
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
International Conference on Learning Representations (ICLR), 2020
Benjamin Eysenbach
Swapnil Asawa
Shreyas Chaudhari
Sergey Levine
Ruslan Salakhutdinov
387
111
0
24 Jun 2020
Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation
International Conference on Machine Learning (ICML), 2020
Masahiro Kato
Takeshi Teshima
362
49
0
12 Jun 2020
Generative Adversarial Networks (GANs Survey): Challenges, Solutions, and Future Directions
ACM Computing Surveys (ACM CSUR), 2020
Divya Saxena
Jiannong Cao
AAML
AI4CE
650
385
0
30 Apr 2020
Robust Generative Adversarial Network
Machine-mediated learning (ML), 2019
Shufei Zhang
Zhuang Qian
Kaizhu Huang
Jimin Xiao
Yuan He
212
16
0
28 Apr 2020
Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator
Yuxuan Song
Qiwei Ye
Minkai Xu
Tie-Yan Liu
144
8
0
05 Apr 2020
Limit Distribution for Smooth Total Variation and
χ
2
χ^2
χ
2
-Divergence in High Dimensions
International Symposium on Information Theory (ISIT), 2020
Ziv Goldfeld
Kengo Kato
190
9
0
03 Feb 2020
Expected Information Maximization: Using the I-Projection for Mixture Density Estimation
International Conference on Learning Representations (ICLR), 2020
P. Becker
Oleg Arenz
Gerhard Neumann
147
16
0
23 Jan 2020
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020
Jie Gui
Zhenan Sun
Yonggang Wen
Dacheng Tao
Jieping Ye
EGVM
315
1,018
0
20 Jan 2020
microbatchGAN: Stimulating Diversity with Multi-Adversarial Discrimination
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2020
Gonçalo Mordido
Haojin Yang
Christoph Meinel
99
24
0
10 Jan 2020
Bridging the Gap Between
f
f
f
-GANs and Wasserstein GANs
International Conference on Machine Learning (ICML), 2019
Jiaming Song
Stefano Ermon
238
44
0
22 Oct 2019
Subsampling Generative Adversarial Networks: Density Ratio Estimation in Feature Space with Softplus Loss
IEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2019
Xin Ding
Z. Jane Wang
William J. Welch
332
20
0
24 Sep 2019
DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning
Journal of Chemical Information and Modeling (JCIM), 2019
Yibo Li
Jianxing Hu
Yanxing Wang
Jielong Zhou
L. Zhang
Zhenming Liu
338
103
0
20 Aug 2019
BreGMN: scaled-Bregman Generative Modeling Networks
Akash Srivastava
Kristjan Greenewald
F. Mirzazadeh
109
6
0
01 Jun 2019
Importance Weighted Hierarchical Variational Inference
Neural Information Processing Systems (NeurIPS), 2019
Artem Sobolev
Dmitry Vetrov
BDL
157
31
0
08 May 2019
Wasserstein-Wasserstein Auto-Encoders
Shunkang Zhang
Yuan Gao
Yuling Jiao
Jin Liu
Yang Wang
Can Yang
DRL
DiffM
86
13
0
25 Feb 2019
Adversarial Learning of a Sampler Based on an Unnormalized Distribution
Chunyuan Li
Ke Bai
Jianqiao Li
Guoyin Wang
Changyou Chen
Lawrence Carin
211
10
0
03 Jan 2019
Latent Dirichlet Allocation in Generative Adversarial Networks
Lili Pan
Shen Cheng
Jian-Dong Liu
Yazhou Ren
Zenglin Xu
GAN
160
3
0
17 Dec 2018
Characterizing and Avoiding Negative Transfer
Computer Vision and Pattern Recognition (CVPR), 2018
Zirui Wang
Zihang Dai
Barnabás Póczós
J. Carbonell
464
462
0
24 Nov 2018
Creating Fair Models of Atherosclerotic Cardiovascular Disease Risk
Stephen Pfohl
Ben J. Marafino
Adrien Coulet
F. Rodriguez
L. Palaniappan
N. Shah
171
74
0
12 Sep 2018
Global Convergence to the Equilibrium of GANs using Variational Inequalities
I. Gemp
Sridhar Mahadevan
254
52
0
04 Aug 2018
Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference
Louis C. Tiao
Edwin V. Bonilla
F. Ramos
BDL
OOD
183
8
0
05 Jun 2018
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning
Jihun Hamm
Yung-Kyun Noh
172
9
0
29 May 2018
Semi-Implicit Variational Inference
Mingzhang Yin
Mingyuan Zhou
BDL
241
143
0
28 May 2018
1
2
Next
