How does LSTM help prevent the vanishing (and exploding) gradient problem in a recurrent neural network?

Answer (1 of 11): There are two factors that affect the magnitude of gradients - the weights and the activation functions (or more precisely, their derivatives) that the gradient passes through. If either of these factors is smaller than 1, then the gradients may vanish in time; if larger than 1...