LSTM — Long Short-Term Memory Networks
LSTMs retain and update a cell state through learned gates. Their gradient path, state handling, and sequential execution define both benefits and limits.
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Squashing Function
Ten maximal sigmoid derivatives multiply to 9.537e-07 and forty to 8.272e-25. These are activation-only factors; the latter is still representable in float32.