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Found 2 papers, 1 papers with code
Online Learning Of Neural Computations From Sparse Temporal Feedback
Using sparse feedback signals that indicate target spike times, and gradient-based parameter updates, we show that the intrinsic parameters can be learned along with the synaptic weights to produce specific input-output functions.
A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network
Instead of experimental data, the rules are constrained by the functions they implement and the structure they are meant to produce.
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