Machine Learning, Neural Network Algorithm, Differential Equations.
represents the network, h(t) is the hidden state at layer t (a vector), and 𝛳(t) are the weights at layer t (a matrix). The hidden state transformation within a residual network is similar and can be formalized as h(t+1) = h(t) + f(h(t), 𝛳(t)). The difference is we add the input to the layer to the