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Codes for the paper 'Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator' ICDM 18
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RemezNet
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pygcn
README.md
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README.md

Rational Neural Networks (RemezNet)

remez net

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},
}
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