Neuromorphic learning, working memory, and metaplasticity in nanowire networks
There are neuromorphic deep learning algorithms. From what I read, one promise of these spiking neural networks is higher efficiency than that of typical neural nets, which would enable learning from much fewer data samples.<p>If anybody here works with SNNs, can you share if you think this claim is true? Also, are there any good entry points for people interested in learning more about SNNs?