Generative Adversarial Networks: Deep Learning in last couple of years have brought us to the brink of next industrial revolution, where AI will impact more than ever in our lives. In this constantly emerging field several new algorithms, architectures and models are being invented. Out of all these Generative Adversarial Network has standout and is being recognized as one ofthe most interesting ideas in last decade in field of ML. In this talk we will share motivation, share past, present and future of applications for GAN's.

1. Oct 27, 2018
Vijay Daultani
Rakuten Institute of Technology
Rakuten, Inc.

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SELF
INTRODUCTION
MOTIVATION
FOR GAN
GENERAL
ARCHITECTURE
654
MOST IMPORTANT
RESEARCH
CONTRIBUTIONS
APPLICATIONS CONCLUSION

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2010
Accenture
2012
IIT Delhi
2014
NEC
2015
UC Berkeley
2017
Rakuten

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𝒙~ 𝒑𝒅𝒂𝒕𝒂 𝒙 𝒛~ 𝒑𝒛( 𝒛)

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0.06 0.05 0.25 0.37 0.08 0.32 0.12
0.19 0.23 0.44 0.04 0.16 0.5 0.48 0.29
0.14 0.37 0 0.16 0.50.27 0.07 0.49
0.17 0.04 0.03 0.29 0.14 0.2 0.22 0.44
0.22 0.17 0.1 0.41 0.01 0.33 0.33
0.50.34 0.34 0.43 0.37 0.39 0.16 0.34
0.22 0.2 0.38 0.06 0.23 0.36 0.42 0.28
0.19 0.32 0.01 0.220.04 0.26 0.24 0.45
0.23 0.28 0.08 0.07 0.18 0.02 0.36
0.47 0.1 0.32 0.43 0.16 0.07 0.07
0.470.04 0.34 0.31 0.12 0.12 0 0.22
0.23 0.2 0.4 0.45 0.19 0.33 0.42 0.08
0.24 0.11 0.2 0.4 0.230.36 0.31 0.01

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童 彤

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References - II