Internal representation dynamics and geometry in recurrent neural networks

9 Jan 2020Stefan HoroiGuillaume LajoieGuy Wolf

The efficiency of recurrent neural networks (RNNs) in dealing with sequential data has long been established. However, unlike deep, and convolution networks where we can attribute the recognition of a certain feature to every layer, it is unclear what "sub-task" a single recurrent step or layer accomplishes... (read more)

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