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Physical Layer Communications System Design Over-the-Air Using
  Adversarial Networks

Physical Layer Communications System Design Over-the-Air Using Adversarial Networks

8 March 2018
Tim O'Shea
Tamoghna Roy
Nathan E. West
Benjamin C. Hilburn
    GAN
ArXiv (abs)PDFHTML

Papers citing "Physical Layer Communications System Design Over-the-Air Using Adversarial Networks"

7 / 7 papers shown
Title
Conditional Mutual Information Neural Estimator
Conditional Mutual Information Neural Estimator
Sina Molavipour
Germán Bassi
Mikael Skoglund
78
14
0
06 Nov 2019
Approximating the Void: Learning Stochastic Channel Models from
  Observation with Variational Generative Adversarial Networks
Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks
Tim O'Shea
Tamoghna Roy
Nathan E. West
GAN
47
129
0
16 May 2018
Backpropagation through the Void: Optimizing control variates for
  black-box gradient estimation
Backpropagation through the Void: Optimizing control variates for black-box gradient estimation
Will Grathwohl
Dami Choi
Yuhuai Wu
Geoffrey Roeder
David Duvenaud
97
300
0
31 Oct 2017
Progressive Growing of GANs for Improved Quality, Stability, and
  Variation
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Tero Karras
Timo Aila
S. Laine
J. Lehtinen
GAN
137
7,361
0
27 Oct 2017
Deep Learning-Based Communication Over the Air
Deep Learning-Based Communication Over the Air
Sebastian Dörner
Sebastian Cammerer
J. Hoydis
S. Brink
63
716
0
11 Jul 2017
An Introduction to Deep Learning for the Physical Layer
An Introduction to Deep Learning for the Physical Layer
Tim O'Shea
J. Hoydis
AI4CE
132
2,198
0
02 Feb 2017
Learning to Communicate: Channel Auto-encoders, Domain Specific
  Regularizers, and Attention
Learning to Communicate: Channel Auto-encoders, Domain Specific Regularizers, and Attention
Tim O'Shea
Kiran Karra
T. Clancy
AI4CE
53
224
0
23 Aug 2016
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