Answers.Body: <p>You are right CNN based models can outperform RNN. You can take a look at this <a href="https://arxiv.org/pdf/1803.01271.pdf" rel="nofollow noreferrer">paper</a> 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 <a href="https://papers.nips.cc/paper/7181-attention-is-all-you-need.pdf" rel="nofollow noreferrer">transformer</a>)  </p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-11-28T09:15:34.997Z
Answers.LastActivityDate: 2019-11-28T09:20:40.883Z
Answers.LastEditDate: 2019-11-28T09:20:40.883Z
Answers.UserDisplayName: razvanc92
Body: <p>Can a CNN (or other non-sequential deep learning models) outperform LSTM (or other sequential models) in time series data? </p>
  
  <p>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.</p>
  
Tags: <machine-learning><convolutional-neural-networks><comparison><long-short-term-memory><time-series>
Title: Can non-sequential deep learning models outperform sequential models in time series forecasting?
UserDisplayName: GiorgosMaragkopoulos
ThreadText: # Can non-sequential deep learning models outperform sequential models in time series forecasting?
  
  (Asked by: username_0 on 2019-11-27)
  
  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.
  
  **Tags:** machine-learning, convolutional-neural-networks, comparison, long-short-term-memory, time-series
  
  
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  ## 1 answers
  
  ### Answer by username_1 on 2019-11-28. Score: 2
  
  You are right CNN based models can outperform RNN. You can take a look at this [paper](https://arxiv.org/pdf/1803.01271.pdf) 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](https://papers.nips.cc/paper/7181-attention-is-all-you-need.pdf))
  
  
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