Stack RNN is a project gathering the code from the paper Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets by Armand Joulin and Tomas Mikolov (pdf). In this research project, we focus on extending Recurrent Neural Networks (RNN) with a stack to allow them to learn sequences which require some form of persistent memory.
Examples are given in the script script_tasks.sh. The code is still under construction. We are working on releasing the code for the list RNN.