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Generative Models and Model Criticism via Optimized Maximum Mean
  Discrepancy

Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy

14 November 2016
Danica J. Sutherland
H. Tung
Heiko Strathmann
Soumyajit De
Aaditya Ramdas
Alex Smola
A. Gretton
ArXivPDFHTML

Papers citing "Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy"

49 / 49 papers shown
Title
Adaptive Latent-Space Constraints in Personalized FL
Adaptive Latent-Space Constraints in Personalized FL
Sana Ayromlou
D. B. Emerson
FedML
49
0
0
12 May 2025
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models
Jialong Jiang
Wenkang Hu
Jian Huang
Yuling Jiao
Xu Liu
DiffM
50
0
0
08 May 2025
Topological Signatures of Adversaries in Multimodal Alignments
Topological Signatures of Adversaries in Multimodal Alignments
Minh Vu
Geigh Zollicoffer
Huy Mai
B. Nebgen
Boian S. Alexandrov
Manish Bhattarai
AAML
65
0
0
29 Jan 2025
A Unified Data Representation Learning for Non-parametric Two-sample Testing
A Unified Data Representation Learning for Non-parametric Two-sample Testing
Xunye Tian
Liuhua Peng
Zhijian Zhou
M. Gong
Feng Liu
Feng Liu
87
0
0
30 Nov 2024
Learning Deep Kernels for Non-Parametric Independence Testing
Learning Deep Kernels for Non-Parametric Independence Testing
Nathaniel Xu
Feng Liu
Danica J. Sutherland
BDL
34
0
0
10 Sep 2024
Neural Approximate Mirror Maps for Constrained Diffusion Models
Neural Approximate Mirror Maps for Constrained Diffusion Models
Berthy T. Feng
Ricardo Baptista
Katherine L. Bouman
MedIm
DiffM
48
3
0
18 Jun 2024
Collaborative non-parametric two-sample testing
Collaborative non-parametric two-sample testing
Alejandro de la Concha
Nicolas Vayatis
Argyris Kalogeratos
26
0
0
08 Feb 2024
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via
  Leverage Scores Sampling
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling
Antoine Chatalic
Nicolas Schreuder
E. De Vito
Lorenzo Rosasco
19
3
0
22 Nov 2023
The Representation Jensen-Shannon Divergence
The Representation Jensen-Shannon Divergence
J. Hoyos-Osorio
Santiago Posso-Murillo
L. S. Giraldo
40
6
0
25 May 2023
A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy
  Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial
  Networks
A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial Networks
Forough Fazeli Asl
M. Zhang
Lizhen Lin
24
1
0
05 Mar 2023
SurvivalGAN: Generating Time-to-Event Data for Survival Analysis
SurvivalGAN: Generating Time-to-Event Data for Survival Analysis
Alexander Norcliffe
B. Cebere
F. Imrie
Pietro Lió
M. Schaar
SyDa
35
14
0
24 Feb 2023
Compress Then Test: Powerful Kernel Testing in Near-linear Time
Compress Then Test: Powerful Kernel Testing in Near-linear Time
Carles Domingo-Enrich
Raaz Dwivedi
Lester W. Mackey
33
9
0
14 Jan 2023
MMD-B-Fair: Learning Fair Representations with Statistical Testing
MMD-B-Fair: Learning Fair Representations with Statistical Testing
Namrata Deka
Danica J. Sutherland
18
6
0
15 Nov 2022
Minimum Kernel Discrepancy Estimators
Minimum Kernel Discrepancy Estimators
Chris J. Oates
27
10
0
28 Oct 2022
Controllable Data Generation by Deep Learning: A Review
Controllable Data Generation by Deep Learning: A Review
Shiyu Wang
Yuanqi Du
Xiaojie Guo
Bo Pan
Zhaohui Qin
Liang Zhao
29
28
0
19 Jul 2022
How Robust is Your Fairness? Evaluating and Sustaining Fairness under
  Unseen Distribution Shifts
How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts
Haotao Wang
Junyuan Hong
Jiayu Zhou
Zhangyang Wang
OOD
56
11
0
04 Jul 2022
PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic
  differential equations
PI-VAE: Physics-Informed Variational Auto-Encoder for stochastic differential equations
Weiheng Zhong
Hadi Meidani
DRL
16
36
0
21 Mar 2022
Geometric Methods for Sampling, Optimisation, Inference and Adaptive
  Agents
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents
Alessandro Barp
Lancelot Da Costa
G. Francca
Karl J. Friston
Mark Girolami
Michael I. Jordan
G. Pavliotis
31
25
0
20 Mar 2022
Robust Bayesian Inference for Simulator-based Models via the MMD
  Posterior Bootstrap
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap
Charita Dellaporta
Jeremias Knoblauch
Theodoros Damoulas
F. Briol
20
42
0
09 Feb 2022
Generating Synthetic Mixed-type Longitudinal Electronic Health Records
  for Artificial Intelligent Applications
Generating Synthetic Mixed-type Longitudinal Electronic Health Records for Artificial Intelligent Applications
Jin Li
B. Cairns
Jingsong Li
T. Zhu
SyDa
38
68
0
22 Dec 2021
Composite Goodness-of-fit Tests with Kernels
Composite Goodness-of-fit Tests with Kernels
Oscar Key
A. Gretton
F. Briol
T. Fernandez
30
14
0
19 Nov 2021
Generative adversarial networks in time series: A survey and taxonomy
Generative adversarial networks in time series: A survey and taxonomy
Eoin Brophy
Zhengwei Wang
Qi She
Tomas E. Ward
EGVM
AI4TS
9
58
0
23 Jul 2021
Standardisation-function Kernel Stein Discrepancy: A Unifying View on
  Kernel Stein Discrepancy Tests for Goodness-of-fit
Standardisation-function Kernel Stein Discrepancy: A Unifying View on Kernel Stein Discrepancy Tests for Goodness-of-fit
Wenkai Xu
32
4
0
23 Jun 2021
Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data
Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data
Feng Liu
Wenkai Xu
Jie Lu
Danica J. Sutherland
15
19
0
14 Jun 2021
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating
  and Auditing Generative Models
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models
Ahmed Alaa
B. V. Breugel
Evgeny S. Saveliev
M. Schaar
50
186
0
17 Feb 2021
Two-sample Test with Kernel Projected Wasserstein Distance
Two-sample Test with Kernel Projected Wasserstein Distance
Jie Wang
Rui Gao
Yao Xie
24
19
0
12 Feb 2021
Benchmarking Simulation-Based Inference
Benchmarking Simulation-Based Inference
Jan-Matthis Lueckmann
Jan Boelts
David S. Greenberg
P. J. Gonçalves
Jakob H. Macke
104
184
0
12 Jan 2021
A kernel test for quasi-independence
A kernel test for quasi-independence
Tamara Fernández
Wenkai Xu
Marc Ditzhaus
A. Gretton
29
2
0
17 Nov 2020
High Resolution Zero-Shot Domain Adaptation of Synthetically Rendered
  Face Images
High Resolution Zero-Shot Domain Adaptation of Synthetically Rendered Face Images
Stephan J. Garbin
Marek Kowalski
Matthew W. Johnson
Jamie Shotton
3DH
25
9
0
26 Jun 2020
Head2Head++: Deep Facial Attributes Re-Targeting
Head2Head++: Deep Facial Attributes Re-Targeting
M. Doukas
Mohammad Rami Koujan
V. Sharmanska
A. Roussos
CVBM
3DH
24
45
0
17 Jun 2020
Learning Deep Kernels for Non-Parametric Two-Sample Tests
Learning Deep Kernels for Non-Parametric Two-Sample Tests
Feng Liu
Wenkai Xu
Jie Lu
Guangquan Zhang
A. Gretton
Danica J. Sutherland
19
176
0
21 Feb 2020
A Review on Generative Adversarial Networks: Algorithms, Theory, and
  Applications
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
Jie Gui
Zhenan Sun
Yonggang Wen
Dacheng Tao
Jieping Ye
EGVM
26
817
0
20 Jan 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
Synthesis of Realistic ECG using Generative Adversarial Networks
Synthesis of Realistic ECG using Generative Adversarial Networks
Anne Marie Delaney
Eoin Brophy
T. Ward
29
79
0
19 Sep 2019
Statistical Inference for Generative Models with Maximum Mean
  Discrepancy
Statistical Inference for Generative Models with Maximum Mean Discrepancy
François‐Xavier Briol
Alessandro Barp
Andrew B. Duncan
Mark Girolami
24
70
0
13 Jun 2019
Unbiased estimators for the variance of MMD estimators
Unbiased estimators for the variance of MMD estimators
Danica J. Sutherland
Namrata Deka
22
11
0
05 Jun 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
Deep Transfer Across Domains for Face Anti-spoofing
Deep Transfer Across Domains for Face Anti-spoofing
X. Tu
Hengsheng Zhang
M. Xie
Yao Luo
Yuefei Zhang
Z. Ma
CVBM
OOD
22
39
0
17 Jan 2019
A witness function based construction of discriminative models using
  Hermite polynomials
A witness function based construction of discriminative models using Hermite polynomials
H. Mhaskar
A. Cloninger
Xiuyuan Cheng
16
9
0
10 Jan 2019
Robustness of Conditional GANs to Noisy Labels
Robustness of Conditional GANs to Noisy Labels
Kerry J. Halupka
A. Khetan
Zinan Lin
Stephen Moore
NoLa
21
79
0
08 Nov 2018
Signature moments to characterize laws of stochastic processes
Signature moments to characterize laws of stochastic processes
I. Chevyrev
Harald Oberhauser
10
108
0
25 Oct 2018
Human Motion Analysis with Deep Metric Learning
Human Motion Analysis with Deep Metric Learning
Huseyin Coskun
D. Tan
Sailesh Conjeti
Nassir Navab
Federico Tombari
11
49
0
30 Jul 2018
Airline Passenger Name Record Generation using Generative Adversarial
  Networks
Airline Passenger Name Record Generation using Generative Adversarial Networks
Alejandro Mottini
Alix Lhéritier
Rodrigo Acuna-Agost
GAN
15
50
0
17 Jul 2018
Quantitatively Evaluating GANs With Divergences Proposed for Training
Quantitatively Evaluating GANs With Divergences Proposed for Training
Daniel Jiwoong Im
He Ma
Graham W. Taylor
K. Branson
EGVM
19
69
0
02 Mar 2018
Demystifying MMD GANs
Demystifying MMD GANs
Mikolaj Binkowski
Danica J. Sutherland
Michael Arbel
A. Gretton
EGVM
43
1,449
0
04 Jan 2018
Associative Domain Adaptation
Associative Domain Adaptation
Philip Häusser
Thomas Frerix
A. Mordvintsev
Daniel Cremers
BDL
13
63
0
02 Aug 2017
Boundary-Seeking Generative Adversarial Networks
Boundary-Seeking Generative Adversarial Networks
R. Devon Hjelm
Athul Paul Jacob
Tong Che
Adam Trischler
Kyunghyun Cho
Yoshua Bengio
GAN
15
170
0
27 Feb 2017
Revisiting Classifier Two-Sample Tests
Revisiting Classifier Two-Sample Tests
David Lopez-Paz
Maxime Oquab
78
390
0
20 Oct 2016
Learning in Implicit Generative Models
Learning in Implicit Generative Models
S. Mohamed
Balaji Lakshminarayanan
GAN
23
412
0
11 Oct 2016
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