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When do you tend to use CNN rather than LSTM (or the other way round) in classification or generation tasks of sequential data like text or log-data? What are the reasons for the decision and what does it depend on? Are there any papers or statistics that confirm this?

I'm thinking of data like Linux log entries or short sentence of length of less than 20 words/tokens.

Personally i would almost always use LSTM but I'm curious if CNN wouldn't be better in some cases, if its possible to implement them in a meaningful way. On short sentence there isn't much buffer to use CNN if i'm not mistaken.

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The networks with one-dimensional convolution over the temporal dimensions are called Temporal Convolutional Networks. The authors of this study claim that TCNs are comparable to RNNs in performance on common tasks associated with RNNs.

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