Highway network

In machine learning, a highway network is an approach to optimizing networks and increasing their depth. Highway networks use learned gating mechanisms to regulate information flow, inspired by Long Short-Term Memory (LSTM) recurrent neural networks. The gating mechanisms allow neural networks to have paths for information to follow across different layers ("information highways").

Highway networks have been used as part of text sequence labeling and speech recognition tasks.