Recurrent Neural Networks
A recurrent neural network (RNN) is a class of artificial neural networks where connections between nodes form a directed graph along a temporal sequence. This allows it to exhibit temporal dynamic behavior. Derived from feedforward neural networks, RNNs can use their internal state (memory) to process variable length sequences of inputs. This makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.[1]
This resource hosts a persistent conversation about academic papers that describe Attention Based Models. This is done by creating a page for each paper in the discussion and writing the relevant questions and comments in the page.