ZHAOZHIHAO / ClusterRouting

Pytorch implementation for the paper of "Capsule networks with non-iterative cluster routing".
MIT License
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Capsule networks with non-iterative cluster routing

A pytorch implementation.

Capsule networks with non-iterative cluster routing
Zhihao Zhao, Samuel Cheng Elsevier Neural Networks, Volume 143, November 2021.

Use this bibtex to cite this repository:

@article{zhao2021capsule,
  title={Capsule networks with non-iterative cluster routing},
  author={Zhao, Zhihao and Cheng, Samuel},
  journal={Neural Networks},
  volume={143},
  pages={690--697},
  year={2021},
  publisher={Elsevier}
}

Prerequisites

This code is tested with the following packages

Training CIFAR10

python3 main.py --dataset cifar10 --C 4 --K 8 --D 24 --batch_size 64 --save_dst ./checkpoint

Training CIFAR10 quickly (less parameters)

python3 main.py --dataset cifar10 --C 4 --K 5 --D 6 --batch_size 64 --save_dst ./checkpoint

Performances

model CIFAR-10 SVHN smallNORB
Dynamic routing 10.6% 4.3% 2.7%
EM routing 11.9% - 1.8%
Cluster routing 7.37% 3.37% 1.57%