Biologically-inspired self-supervised systems

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Project members: ,
Start date: 1. January 2022
End date:
Funding source: Internally funded

Abstract

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.