Why do we need Recurrent Neural Network? Math in a Vanilla Recurrent Neural Network three equations, incrementing t at each step
rnn_tutorial.pdf
Discrete, time-independent difference equations of RNN state and output: ? + 1 = analogue to standard backpropagation used in
bianchi.pdf
Technically, an RNN models sequences The Final Backpropagation Equation Geoffrey et al, “Improving Performance of Recurrent Neural Network with ReLU
lec20_rnn.pdf
13 nov 2001 · well with a discrete time recurrent neural network To simplify notation we will restrict equations to include two-layered networks,
RNN_Intro.pdf
LSTM [9] in particular is an RNN architecture that has excelled in sequence generation [3, 13, 4], speech recognition [5] and reinforcement learning [12, 10]
6221-memory-efficient-backpropagation-through-time.pdf
The propagation of activation in these networks is determined by dissipative differential equations The error signal is backpropagated by integrating an
735b90b4568125ed6c3f678819b6e058-Paper.pdf
Short presentation on update of LSTM layer design and doubts Computes input gate values according to equation: backpropagation in LSTM cell Fig 2
Recurrent_Neural_Networks_LSTM__Part-2.pdf