%0 Generic %1 zhao2018information %A Zhao, Tianchen %A Sun, Yuekai %D 2018 %K 2018 arxiv deep-learning information-theory paper %T Information Theoretic Interpretation of Deep learning %U http://arxiv.org/abs/1803.07980 %X We interpret part of the experimental results of Shwartz-Ziv and Tishby 2017. Inspired by these results, we established a conjecture of the dynamics of the machinary of deep neural network. This conjecture can be used to explain the counterpart result by Saxe et al. 2018.

@misc{zhao2018information, abstract = {We interpret part of the experimental results of Shwartz-Ziv and Tishby [2017]. Inspired by these results, we established a conjecture of the dynamics of the machinary of deep neural network. This conjecture can be used to explain the counterpart result by Saxe et al. [2018].}, added-at = {2018-03-22T16:47:39.000+0100}, author = {Zhao, Tianchen and Sun, Yuekai}, biburl = {https://www.bibsonomy.org/bibtex/2c7d09b8db72844b9fb597b63a81d2ce1/achakraborty}, description = {[1803.07980] Information Theoretic Interpretation of Deep learning}, interhash = {5deff883b1ac978d68544cdd6bfcdc64}, intrahash = {c7d09b8db72844b9fb597b63a81d2ce1}, keywords = {2018 arxiv deep-learning information-theory paper}, note = {cite arxiv:1803.07980Comment: 17 pages, 7 figures}, timestamp = {2018-03-22T16:47:39.000+0100}, title = {Information Theoretic Interpretation of Deep learning}, url = {http://arxiv.org/abs/1803.07980}, year = 2018 }