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Learning Generative Models of Structured Signals from Their
  Superposition Using GANs with Application to Denoising and Demixing

Learning Generative Models of Structured Signals from Their Superposition Using GANs with Application to Denoising and Demixing

12 February 2019
Mohammadreza Soltani
Swayambhoo Jain
Abhinav V. Sambasivan
    GAN
    DiffM
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Papers citing "Learning Generative Models of Structured Signals from Their Superposition Using GANs with Application to Denoising and Demixing"

2 / 2 papers shown
Title
Generative Adversarial Source Separation
Generative Adversarial Source Separation
Cem Subakan
Paris Smaragdis
GAN
122
67
0
30 Oct 2017
Learning a Probabilistic Latent Space of Object Shapes via 3D
  Generative-Adversarial Modeling
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
Jiajun Wu
Chengkai Zhang
Tianfan Xue
Bill Freeman
J. Tenenbaum
GAN
171
1,940
0
24 Oct 2016
1