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On the same problems, sometimes GRU is better, sometimes LSTM. In short, having more parameters (more "knobs") is not always a good thing. The training process needs to learn those parameters. There is a higher chance of over-fitting, amongst other problems. The parameters are assigned specific roles inside either GRU or LSTM, so if that role is less ...


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