Biologically inspired alternatives to backpropagation through time for
learning in recurrent neural nets
G. Bellec, F. Scherr, E. Hajek, D. Salaj, R. Legenstein, and W. Maass. (2019)cite arxiv:1901.09049Comment: We changed in this version 2 of the paper the name of the new learning algorithms to e-prop, corrected minor errors, added details -- especially for resulting new rules for synaptic plasticity, edited the notation, and included new results for TIMIT.
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