Search Results for author:
Found 1 papers, 0 papers with code
Unsupervised End-to-End Training with a Self-Defined Bio-Inspired Target
Current unsupervised learning methods depend on end-to-end training via deep learning techniques such as self-supervised learning, with high computational requirements, or employ layer-by-layer training using bio-inspired approaches like Hebbian learning, using local learning rules incompatible with supervised learning.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
