Can a CNN (or other non-sequential deep learning models) outperform LSTM (or other sequential models) in time series data?
I know this question is not very specific, but I experienced this when predicting daily store sales and I am curious as to why it can happen.
You are right CNN based models can outperform RNN. You can take a look at this paper where they compared different RNN models with TCN (temporal convolutional networks) on different sequence modeling tasks. Even though there are no big differences in terms of results there are some nice properties that CNN based models offers such as: parallelism, stable gradients and low training memory footprint. In addition to CNN based models there are also attention based models (you might want to take a look at the transformer)
