Biologically-inspired self-supervised systems
Project members: ,
Start date: 1. January 2022
Funding source: Internally funded
The aim of this project is to develop self-supervised learning systems under biological constraints. This has the twofold advantage of providing biologically plausible computational models, as well as delivering more interpretable decision makers, capable of operating under resource-constrained conditions.