The Architecture of Memory: Design and Applications of Recurrent Neural Networks
From Google Translate to Siri, RNNs power language modeling and machine translation. They understand that the meaning of a word depends on the words that came before it. Recurrent Neural Networks Design And Applications
Converting acoustic signals into text requires the network to interpret a continuous stream of sound, where the phonemes are deeply interconnected. The Architecture of Memory: Design and Applications of
A streamlined version of the LSTM that merges gates for efficiency while maintaining similar performance. Diverse Applications A streamlined version of the LSTM that merges
The defining feature of an RNN design is the hidden state, often described as the network's "memory." Unlike a standard network that maps an input to an output , an RNN maps (input at time ht−1h sub t minus 1 end-sub (the previous hidden state) to a new hidden state