This project correspond to the paper Rui Zhang, Ziheng Jiao, Hongyuan Zhang, and Xuelong Li, "Manifold Neural Network With Non-Gradient Optimization." IEEE Trans. Pattern Anal. Tntell. 45(3): 3986-3993 (2023).
Please kindly cite our paper if you use this code in your own work:
@ARTICLE{9773979,
author={Zhang, Rui and Jiao, Ziheng and Zhang, Hongyuan and Li, Xuelong},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={Manifold Neural Network With Non-Gradient Optimization},
year={2023},
volume={45},
number={3},
pages={3986-3993},
doi={10.1109/TPAMI.2022.3174574}}
Ziheng Jiao and Hongyuan Zhang
The model and comparison models in paper "Non-Gradient Manifold Neural Network" are all implemented with Pytorch 1.2.0, CUDA 10.0 on Windows 10 PC. The following packages you need is several well-known ones, including:
- python==3.6
- pytorch==1.2.0
- torchvision==0.4.0
- numpy==1.19.1
- scipy==1.2.1
- scikit-learn==0.19.2
- model.py: the framework code of the proposed model.
- load_data.py: code to load data.
- utils.py: functions used in experiemnts.
- data: training and testing datasets.
- train.py: the training code.
You can test the code by the following command
python train.py