[ICLR 2023] Official PyTorch implementation for "Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint".
This paper proposes Bort, an optimizer for improving model explainability with boundedness and orthogonality constraints on model parameters, derived from the sufficient conditions of model comprehensibility and invertibility.
pip install -r requirements.txt
pip install -e .If you find this work helpful, please cite our paper:
@inproceedings{zhang2023bort,
title={Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint},
author={Zhang, Borui and Zheng, Wenzhao and Zhou, Jie and Lu, Jiwen},
booktitle={The Eleventh International Conference on Learning Representations},
year={2023}
}