12 citations · 15 across the 4 of their papers we have counts for
3 papers · 1 filter
A Review of Neuroscience-Inspired Machine Learning
Alexander Ororbia, Ankur Mali, Adam Kohan +2
One major criticism of deep learning centers around the biological implausibility of the credit assignment schema used for learning -- backpropagation of errors. This implausibilit…
Temporal Weights
Adam Kohan, Ed Rietman, Hava Siegelmann
In artificial neural networks, weights are a static representation of synapses. However, synapses are not static, they have their own interacting dynamics over time. To instill wei…
Error Forward-Propagation: Reusing Feedforward Connections to Propagate Errors in Deep Learning
Adam A. Kohan, Edward A. Rietman, Hava T. Siegelmann
We introduce Error Forward-Propagation, a biologically plausible mechanism to propagate error feedback forward through the network. Architectural constraints on connectivity are vi…