Authors: Marcel van Gerven, Nasir Ahmad, Sander Dalm, Kieran Carrigg

This repository implements decorrelated backpropagation. To run a model with and without backpropagation, use experiments/main in combination with a config file (experiments/config).

When using the decorrelation code please cite this repository (https://github.com/artcogsys/decorbp) and the following papers:

Ahmad, N., Schrader, E., & van Gerven, M. (2023). Constrained parameter inference as a principle for learning. Transactions on Machine Learning Research, 1–18.

Dalm, S., Offergeld, J., Ahmad, N., & van Gerven, M. (2024). Efficient deep learning with decorrelated backpropagation. arXiv. https://arxiv.org/abs/2405.02385

Carrigg, K., van Gastel, R., Yeghaian, M., Dalm, S., Boughorbel, F., & van Gerven, M. (2025). Decorrelation Speeds Up Vision Transformers. arXiv preprint arXiv:2510.14657