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Memory inside sequence models
March 15, 2024, 8:51 p.m. | /u/Sinestro101
Deep Learning www.reddit.com
Aside the architectural differences between the plain RNN, GRU and LSTM, memory is basically the input sequence being processed through some mathematical function and served in a sequential manner as input to the next time step (along input Xt) sort of as a prior representation of the data.
From this technical perspective memory seems constrained to the length of the …
concept deeplearning differences function gru inside lstm memory next rnn through transformers understanding variants
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