Golden
Recurrent neural network

Recurrent neural network

A class of artificial neural network where connections between units form a directed cycle

Recurrent neural network (RNN) is a class of artificial neural network that utilizes information arbitrarily in long sequences. It represents history by neurons with recurrent connections. It can learn to compress unlimited history in low dimensional space. Contrary to the traditional neural network that all inputs and outputs are independent of each other.



Recurrent networks have the capability to form short term memory that enable them to deal with position invariance which feedforward networks cannot do. RNNs are called recurrent due to its performance of the same task for every element of a sequence with the output being depended on the previous computations.

Timeline

People

Name
Role
Related Golden topics







Further reading

Title
Author
Link
Type
Date

Attention and Augmented Recurrent Neural Networks



Web



Sequence Modeling: Recurrent

and Recursive Nets

Ian Goodfellow, Yoshua Bengio, Aaron Courville

Book Chapter

2016

Documentaries, videos and podcasts

Title
Date
Link

Stanford University School of Engineering: Lecture 10 | Recurrent Neural Networks

2017

Companies

Company
CEO
Location
Products/Services