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Several recent works in communication systems have proposed to leverage the power of neural networks in the design of encoders and decoders.
M. D. Donsker and S. S. Varadhan, “Asymptotic evaluation of certain Markov process expectations for large time. I,”
1975
Earlier work this paper cites.
N. Tishby, F. C. Pereira, and W. Bialek, “The information bottleneck method,” in
1999
Earlier work this paper cites.
L. Paninski, “Estimation of entropy and mutual information,”
2003
Earlier work this paper cites.
D. Barber and F. V. Agakov, “The IM algorithm: a variational approach to information maximization,” in
2003
Earlier work this paper cites.
A. Kraskov, H. Stögbauer, and P. Grassberger, “Estimating mutual information,”
2004
Earlier work this paper cites.
S. Frenzel and B. Pompe, “Partial mutual information for coupling analysis of multivariate time series,”
2007
Earlier work this paper cites.
M. Vejmelka and M. Paluš, “Inferring the directionality of coupling with conditional mutual information,”
2008
Earlier work this paper cites.
Q. Wang, S. R. Kulkarni, and S. Verdú, “Universal estimation of information measures for analog sources,”
2009
Earlier work this paper cites.
2010
Earlier work this paper cites.
A. El Gamal and Y.-H. Kim,
2011
Earlier work this paper cites.
C. J. Quinn, T. P. Coleman, N. Kiyavash, and N. G. Hatsopoulos, “Estimating the directed information to infer causal relationships in ensemble neural spike train recordings,”
2011
Cited alongside, same era.
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative adversarial nets,” in
2014
Cited alongside, same era.
S. Nowozin, B. Cseke, and R. Tomioka, “F-GAN: Training generative neural samplers using variational divergence minimization,” in
2016
Cited alongside, same era.
S. Molavipour, G. Bassi, and M. Skoglund, “Testing for directed information graphs,” in
2017
Cited alongside, same era.
T. Tanaka, H. Sandberg, and M. Skoglund, “Transfer-entropy-regularized markov decision processes,”
2017
Cited alongside, same era.
M. I. Belghazi, A. Baratin, S. Rajeshwar, S. Ozair, Y. Bengio, A. Courville, and D. Hjelm, “MINE: Mutual Information Neural Estimation,” in
2018
Later among the works it cites.
W. Gao, S. Oh, and P. Viswanath, “Demystifying fixed
2018
Later among the works it cites.
J. Runge, “Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information,” in
2018
Later among the works it cites.
2018
Later among the works it cites.
B. Poole, S. Ozair, A. van den Oord, A. A. Alemi, and G. Tucker, “On variational lower bounds of mutual information,” in
2018
Later among the works it cites.
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T. O’Shea and J. Hoydis, “An introduction to deep learning for the physical layer,”
2017
Cited alongside, same era.
M. Gabrié, A. Manoel, C. Luneau, N. Macris, F. Krzakala, L. Zdeborová
2018
Cited alongside, same era.
S. Dörner, S. Cammerer, J. Hoydis, and S. ten Brink, “Deep learning based communication over the air,”
2018
Cited alongside, same era.
H. Ye, G. Y. Li, B.-H. F. Juang, and K. Sivanesan, “Channel agnostic end-to-end learning based communication systems with conditional GAN,” in
2018
Cited alongside, same era.
T. J. O’Shea, T. Roy, N. West, and B. C. Hilburn, “Physical layer communications system design over-the-air using adversarial networks,” in
2018
Cited alongside, same era.
2018
Later among the works it cites.
R. D. Hjelm, A. Fedorov, S. Lavoie-Marchildon, K. Grewal, P. Bachman, A. Trischler, and Y. Bengio, “Learning deep representations by mutual information estimation and maximization,” in
2019
Closest in time.
R. Fritschek, R. F. Schaefer, and G. Wunder, “Deep learning for the Gaussian wiretap channel,” in
2019
Closest in time.
R. Fritschek, R. F. Schaefer, and G. Wunder, “Deep learning for channel coding via neural mutual information estimation,” in
2019
Closest in time.