 Recurrent neural network

A neural network whose hidden state follows a recurrence $h_t=F(h_{t-1},x_t)$ with shared parameters. It represents dependence across sequence positions through its hidden state. The standard recurrence is sequential across positions, and differentiation through many steps multiplies step Jacobian matrices, potentially causing a vanishing gradient or an exploding gradient.