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TreeRNN

TreeRNN is a small experimental (unregistered) package implementing variants of recurrent neural networks (RNNs) for tree-structured data. The input tree-structured data are assumed to be in the JSON format. The package was used to compute the tree RNNs in the following paper: Papež M, Rektoris M, Šmídl V, Pevný T. Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs. In The 12th International Conference on Learning Representations (ICLR2024).

The package is built on top of JSONGrinder.jl and Mill.jl.

To use the package, execute the following steps.

  1. Clone this repository.
git clone https://github.com/mlnpapez/TreeRNN.jl TreeRNN.jl
  1. Go to the TreeRNN.jl repository.
cd TreeRNN.jl
  1. Open the Julia 1.10.2 console and write:
using Pkg
Pkg.activate(".")
Pkg.instantiate()
  1. Use the package:
using TreeRNN

The repository contains 12 datasets in JSON format (listed in the table below). All these datasets were downloaded from CTU Prague Relational Learning Repository and converted into the JSON format.

Dataset         # of instances # of classes
mutagenesis     188             2            
genes           862             15          
cora             2708           7            
citeseer         3312           6            
webkp           877             5            
world           239             7            
chess           295             3            
uw_cse           278             4            
hepatitis       500             2            
ftp             30000           3            
ptc             343             2            
dallas           219             7            

The repository currently contains three models (listed in the table below).

Model     Description                             Reference
TreeGRU   tree-structured gated reccurent unit   https://arxiv.org/abs/1610.02806
TreeLSTM tree-structured long short-term memory https://arxiv.org/abs/1503.00075
TreeMLP   tree-structured multilayer perceptron   -

Execute the following steps to train one of these models on a selected dataset.

  1. Go to the TreeRNN.jl repository.
cd TreeRNN.jl
  1. Open the Julia 1.10.2 console and write:
using Pkg
Pkg.activate("scripts")
Pkg.instantiate()
Pkg.develop(path=".")
  1. Use the package:
include("scripts/train.jl")