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2012.00780
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Refining Deep Generative Models via Discriminator Gradient Flow
International Conference on Learning Representations (ICLR), 2020
1 December 2020
Abdul Fatir Ansari
Ming Liang Ang
Harold Soh
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Papers citing
"Refining Deep Generative Models via Discriminator Gradient Flow"
33 / 33 papers shown
Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach
Haoxuan Chen
Yinuo Ren
Martin Renqiang Min
Lexing Ying
Zachary Izzo
DiffM
MedIm
527
14
0
04 Jun 2025
Improving Discriminator Guidance in Diffusion Models
Alexandre Verine
Mehdi Inane
Florian Le Bronnec
Benjamin Négrevergne
Y. Chevaleyre
DiffM
356
2
0
20 Mar 2025
Inclusive KL Minimization: A Wasserstein-Fisher-Rao Gradient Flow Perspective
Jia-Jie Zhu
525
4
0
31 Oct 2024
Don't Start from Scratch: Behavioral Refinement via Interpolant-based Policy Diffusion
Kaiqi Chen
Eugene Lim
Kelvin Lin
Yiyang Chen
Harold Soh
DiffM
466
21
0
25 Feb 2024
Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport
Jaemoo Choi
Jaewoong Choi
Myungjoo Kang
474
19
0
08 Feb 2024
Neural Sinkhorn Gradient Flow
Huminhao Zhu
Fangyikang Wang
Chao Zhang
Han Zhao
Hui Qian
253
9
0
25 Jan 2024
Optimal Budgeted Rejection Sampling for Generative Models
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Alexandre Verine
Muni Sreenivas Pydi
Benjamin Négrevergne
Y. Chevaleyre
424
5
0
01 Nov 2023
Bridging the Gap Between Variational Inference and Wasserstein Gradient Flows
Mingxuan Yi
Song Liu
DRL
265
10
0
31 Oct 2023
Analyzing and Improving Optimal-Transport-based Adversarial Networks
International Conference on Learning Representations (ICLR), 2023
Jaemoo Choi
Jaewoong Choi
Myungjoo Kang
OT
374
7
0
04 Oct 2023
Module-wise Training of Neural Networks via the Minimizing Movement Scheme
Neural Information Processing Systems (NeurIPS), 2023
Skander Karkar
Bhaskar Sen
Emmanuel de Bezenac
Patrick Gallinari
373
4
0
29 Sep 2023
Diffusion Models with Deterministic Normalizing Flow Priors
Mohsen Zand
Ali Etemad
Michael A. Greenspan
DiffM
466
7
0
03 Sep 2023
Don't be so negative! Score-based Generative Modeling with Oracle-assisted Guidance
International Conference on Machine Learning (ICML), 2023
Saeid Naderiparizi
Xiaoxuan Liang
Setareh Cohan
Berend Zwartsenberg
Frank Wood
DiffM
290
7
0
31 Jul 2023
Insights into Closed-form IPM-GAN Discriminator Guidance for Diffusion Modeling
Aadithya Srikanth
Siddarth Asokan
Nishanth Shetty
C. Seelamantula
384
0
0
02 Jun 2023
Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models
Neural Information Processing Systems (NeurIPS), 2023
Weijian Luo
Tianyang Hu
Shifeng Zhang
Jiacheng Sun
Zhenguo Li
Zhihua Zhang
356
210
0
29 May 2023
Unifying GANs and Score-Based Diffusion as Generative Particle Models
Neural Information Processing Systems (NeurIPS), 2023
Jean-Yves Franceschi
Mike Gartrell
Ludovic Dos Santos
Thibaut Issenhuth
Emmanuel de Bezenac
Mickaël Chen
A. Rakotomamonjy
DiffM
397
28
0
25 May 2023
Generative Modeling through the Semi-dual Formulation of Unbalanced Optimal Transport
Neural Information Processing Systems (NeurIPS), 2023
Jaemoo Choi
Jaewoong Choi
Myung-joo Kang
OT
681
36
0
24 May 2023
Generative Sliced MMD Flows with Riesz Kernels
International Conference on Learning Representations (ICLR), 2023
J. Hertrich
Christian Wald
Fabian Altekrüger
Paul Hagemann
384
38
0
19 May 2023
TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation
International Conference on Machine Learning (ICML), 2023
Zhaoyan Liu
Noël Vouitsis
S. Gorti
Jimmy Ba
Gabriel Loaiza-Ganem
ViT
387
2
0
26 Apr 2023
A mean-field games laboratory for generative modeling
Benjamin J. Zhang
Markos A. Katsoulakis
663
32
0
26 Apr 2023
Generative Modeling with Flow-Guided Density Ratio Learning
Alvin Heng
Abdul Fatir Ansari
Harold Soh
302
1
0
07 Mar 2023
Learning Probabilistic Models from Generator Latent Spaces with Hat EBM
Neural Information Processing Systems (NeurIPS), 2022
Mitch Hill
Erik Nijkamp
Jonathan Mitchell
Bo Pang
Song-Chun Zhu
839
14
0
29 Oct 2022
Block-wise Training of Residual Networks via the Minimizing Movement Scheme
Skander Karkar
Ibrahim Ayed
Emmanuel de Bézenac
Patrick Gallinari
248
1
0
03 Oct 2022
Maximum Likelihood Training of Implicit Nonlinear Diffusion Models
Neural Information Processing Systems (NeurIPS), 2022
Dongjun Kim
Byeonghu Na
S. Kwon
Dongsoo Lee
Wanmo Kang
Il-Chul Moon
DiffM
720
60
0
27 May 2022
GANs as Gradient Flows that Converge
Journal of machine learning research (JMLR), 2022
Yu‐Jui Huang
Yuchong Zhang
320
6
0
05 May 2022
Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders
International Conference on Learning Representations (ICLR), 2022
Huangjie Zheng
Pengcheng He
Weizhu Chen
Mingyuan Zhou
DiffM
344
55
0
19 Feb 2022
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
Zhisheng Xiao
Karsten Kreis
Arash Vahdat
DiffM
529
701
0
15 Dec 2021
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion
Tim Dockhorn
Arash Vahdat
Karsten Kreis
DiffM
765
273
0
14 Dec 2021
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory
International Conference on Learning Representations (ICLR), 2021
T. Chen
Guan-Horng Liu
Evangelos A. Theodorou
DiffM
OT
733
239
0
21 Oct 2021
Controllable and Compositional Generation with Latent-Space Energy-Based Models
Neural Information Processing Systems (NeurIPS), 2021
Weili Nie
Arash Vahdat
Anima Anandkumar
289
87
0
21 Oct 2021
Rethinking Multidimensional Discriminator Output for Generative Adversarial Networks
M. Dai
Haibin Hang
A. Srivastava
277
3
0
08 Sep 2021
BIGRoC: Boosting Image Generation via a Robust Classifier
Roy Ganz
Michael Elad
291
11
0
08 Aug 2021
Score-based Generative Modeling in Latent Space
Neural Information Processing Systems (NeurIPS), 2021
Arash Vahdat
Karsten Kreis
Jan Kautz
DiffM
567
833
0
10 Jun 2021
EBMs Trained with Maximum Likelihood are Generator Models Trained with a Self-adverserial Loss
Zhisheng Xiao
Qing Yan
Y. Amit
288
3
0
23 Feb 2021
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