Skip to content

aquastar/RationalGraphNet

master
Switch branches/tags
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 
 
 

Demo of Rational Net in spectral domain

func: the target function to approximate
fit: rational function by nerual networks
approximation by rational neural networks

Rational Neural Network for Graph Signal Prediction

Instruction (under construction)

install required python package

pip install -r requirements.txt  

Choose on pre-processed datasets (Default is 1st below):

data switch can be configured by pass dataset index in remez_net.py

gen_data(data=1)

Then, run the main program:

python remez_net.py  

GCN configuration is also provided. To perform regression task and compare fairly, neural network weights are removed:

python pygcn/train.py  

MSE

RationalNet GCN
America 0.0236 1.3641
crime 0.26021 1.0605
language 0.0329 0.3912

Related papar

Codes for the paper

Zhiqian Chen, Feng Chen, Rongjie Lai, Xuchao Zhang, and Chang-Tien Lu, Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator, International Conference on Data Mining(ICDM), Singpore, 2018

Citation

@article{chen2018icdmrationalnet
  author    = {Zhiqian Chen and
               Feng Chen and
               Rongjie Lai and
               Xuchao Zhang and
               Chang{-}Tien Lu},
  title     = {Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator},
  booktitle = {Proceedings of the The IEEE International Conference on Data Mining},
  year      = {2018},
}

About

Codes for the paper 'Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator' ICDM 18

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages