8 citations · 9 across the 3 of their papers we have counts for
3 papers
q-bio.NC2024★ 1 cited
Heterogeneous quantization regularizes spiking neural network activity
Roy Moyal, Kyrus R. Mama, Matthew Einhorn +2
The learning and recognition of object features from unregulated input has been a longstanding challenge for artificial intelligence systems. Brains are adept at learning stable re…
cs.NE2022
Sapinet: A sparse event-based spatiotemporal oscillator for learning in the wild
Ayon Borthakur
We introduce Sapinet -- a spike timing (event)-based multilayer neural network for \textit{learning in the wild} -- that is: one-shot online learning of multiple inputs without cat…
cs.NE2019★ 8 cited
Signal Conditioning for Learning in the Wild
Ayon Borthakur, Thomas A. Cleland
The mammalian olfactory system learns rapidly from very few examples, presented in unpredictable online sequences, and then recognizes these learned odors under conditions of subst…