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The estimation of mutual information (MI) or conditional mutual information (CMI) from a set of samples is a long-standing problem.
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M. Vejmelka and M. Paluš, “Inferring the directionality of coupling with conditional mutual information,” Physical Review E , vol. 77, no. 2, p. 026214, Feb. 2008
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Q. Wang, S. R. Kulkarni, and S. Verdú, “Universal estimation of information measures for analog sources,” Foundations and Trends® in Communications and Information Theory , vol. 5, no. 3, pp. 265–353, 2009
2009
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X. Nguyen, M. J. Wainwright, and M. I. Jordan, “Estimating divergence functionals and the likelihood ratio by convex risk minimization,” IEEE Trans. Inf. Theory , vol. 56, no. 11, pp. 5847–5861, Nov. 2010
2010
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A. El Gamal and Y.-H. Kim, Network information theory . Cambridge University Press, 2011
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I. Goodfellow, Y. Bengio, and A. Courville, Deep learning . MIT press, 2016
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S. Molavipour, G. Bassi, and M. Skoglund, “Testing for directed information graphs,” in 55th Annual Allerton Conf. on Comm., Control, Comput. (Allerton) , Oct. 2017, pp. 212–219
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T. O’Shea and J. Hoydis, “An introduction to deep learning for the physical layer,” IEEE Trans. on Cogn. Commun. Netw. , vol. 3, no. 4, pp. 563–575, Dec. 2017
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2019
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B. Poole, S. Ozair, A. Van Den Oord, A. Alemi, and G. Tucker, “On variational bounds of mutual information,” ser. Proc. of Machine Learning Research, vol. 97. PMLR, Jun 2019, pp. 5171–5180
2019
Later among the works it cites.
S. Mukherjee, H. Asnani, and S. Kannan, “CCMI: Classifier based conditional mutual information estimation,” in Uncertainty in Artificial Intelligence , Jul. 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
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W. Gao, S. Oh, and P. Viswanath, “Demystifying fixed k k -nearest neighbor information estimators,” IEEE Trans. Inf. Theory , vol. 64, no. 8, pp. 5629–5661, Aug. 2018
2018
Cited alongside, same era.
J. Runge, “Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information,” in 21st Int. Conf. Art. Intell. Stats. (AISTATS) , Apr. 2018, pp. 938–947
2018
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 35th Int. Conf. Mach. Learn. (ICML) , Jul. 2018, pp. 531–540
2018
Cited alongside, same era.
2018
Cited alongside, same era.
S. Dörner, S. Cammerer, J. Hoydis, and S. ten Brink, “Deep learning based communication over the air,” IEEE J. Sel. Topics Signal Process. , vol. 12, no. 1, pp. 132–143, Feb. 2018
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 26th European Signal Process. Conf. (EUSIPCO) , Sep. 2018, pp. 529–532
2018
Cited alongside, same era.
2019
Later among the works it cites.
2019
Later among the works it cites.
R. Fritschek, R. F. Schaefer, and G. Wunder, “Deep learning for channel coding via neural mutual information estimation,” in 2019 IEEE 20th Int. Workshop Signal Process. Adv. Wireless Commun. (SPAWC) , Jul. 2019
2019
Later among the works it cites.
2020
Closest in time.
S. Molavipour, G. Bassi, and M. Skoglund, “Conditional mutual information neural estimator,” in 2020 IEEE Int. Conf. Acoust., Speech, Signal Process. (ICASSP) , May 2020, pp. 5025–5029
2020
Closest in time.
2020
Closest in time.