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Learning Implicit Generative Models with Theoretical Guarantees
v1v2 (latest)

Learning Implicit Generative Models with Theoretical Guarantees

7 February 2020
Yuan Gao
Jian Huang
Yuling Jiao
Jin Liu
ArXiv (abs)PDFHTML

Papers citing "Learning Implicit Generative Models with Theoretical Guarantees"

5 / 5 papers shown
Refining 6-DoF Grasps with Context-Specific Classifiers
Refining 6-DoF Grasps with Context-Specific ClassifiersIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2023
Tasbolat Taunyazov
Heng Zhang
John Patrick Eala
Na Zhao
Harold Soh
225
3
0
14 Aug 2023
GANs as Gradient Flows that Converge
GANs as Gradient Flows that ConvergeJournal of machine learning research (JMLR), 2022
Yu‐Jui Huang
Yuchong Zhang
330
6
0
05 May 2022
Refining Deep Generative Models via Discriminator Gradient Flow
Refining Deep Generative Models via Discriminator Gradient FlowInternational Conference on Learning Representations (ICLR), 2020
Abdul Fatir Ansari
Ming Liang Ang
Harold Soh
435
51
0
01 Dec 2020
Deep Dimension Reduction for Supervised Representation Learning
Deep Dimension Reduction for Supervised Representation LearningIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Jian Huang
Yuling Jiao
Xu Liao
Jin Liu
Zhou Yu
DRL
280
22
0
10 Jun 2020
Tessellated Wasserstein Auto-Encoders
Tessellated Wasserstein Auto-Encoders
Kuo Gai
Shihua Zhang
DRL
204
1
0
20 May 2020
1
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