This is the official Pytorch implementation of "Multi-layered tensor networks for image classification", Raghavendra Selvan et al. 2020
- Run and reproduce results in the paper on LIDC dataset
- v1.0
- Basic Pytorch dependency
- Tested on Pytorch 1.3, Python 3.6
- Download the data from here
- Unzip the data and point the path to --data_path
- How to run tests: python train.py --data_path data_location --mltn --bn
- Kindly cite our publication if you use any part of the code
@misc{raghav2020mltn,
title={Multi-layered tensor networks for image classification},
author={Raghavendra Selvan, Silas Ørting and Erik B Dam},
howpublished={First Workshop on Quantum Tensor Networks in Machine Learning. In conjunction with 34th NeurIPS},
month={Dec},
url={https://arxiv.org/abs/2011.06982},
note={arXiv:2011.06982},
year={2020}}
- Torch MPS for the amazing MPS in Pytorch implementations
- Prob.U-Net for preprocessing LIDC data
- Dense Net implementation