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TensorFlow allows you to create MultiRNNCell composed sequentially of multiple simple cells (LSTM and GRU). I usually use same type of cell when creating MultiRNNCell but I was wondering if there could be some benefits in using both LSTM and GRU? Does anyone have some experience with it or theoretical insights?

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    $\begingroup$ Would be pretty interesting to see. I might be testing the combination of LSTM and NARX cells. $\endgroup$ – Thomas W May 11 '17 at 8:41
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There are some thousands of variants of RNN cell(kernel) and both LSTM and GRU are for processing the input $x_i$ and the output of the previous state $s_{i-1}$ and producing the output and the current state. Even thought LSTM preceded GRU and GRU contains less computation, LSTM is just on a par with GRU in performance. So, I think stacking LSTM and GRU or any other cells might just interesting but would not make any big difference in improving the performance.

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  • $\begingroup$ +1 for the last sentence: they really don't do things that are that different so there's not that much advantage you'd get from combining them. $\endgroup$ – Wayne Feb 8 '18 at 14:18
  • $\begingroup$ When you say that LSTM is on par with GRU, are you making the comparison on a per-unit basis or a per-parameter basis? $\endgroup$ – Sycorax Feb 8 '18 at 14:59

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