6 citations · 21 across the 13 of their papers we have counts for
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cs.NE2023
Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry
Bariscan Bozkurt, Cengiz Pehlevan, Alper T Erdogan
The backpropagation algorithm has experienced remarkable success in training large-scale artificial neural networks; however, its biological plausibility has been strongly criticiz…
cs.NE2019★ 2 cited
Structured and Deep Similarity Matching via Structured and Deep Hebbian Networks
Dina Obeid, Hugo Ramambason, Cengiz Pehlevan
Synaptic plasticity is widely accepted to be the mechanism behind learning in the brain's neural networks. A central question is how synapses, with access to only local information…
cs.NE2019
A Spiking Neural Network with Local Learning Rules Derived From Nonnegative Similarity Matching
Cengiz Pehlevan
The design and analysis of spiking neural network algorithms will be accelerated by the advent of new theoretical approaches. In an attempt at such approach, we provide a principle…