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Found 3 papers, 1 papers with code
Cortico-cerebellar networks as decoupling neural interfaces
Recently, decoupled neural interfaces (DNIs) were introduced as a solution to the forward and feedback locking problems in deep networks.
Current State and Future Directions for Learning in Biological Recurrent Neural Networks: A Perspective Piece
We provide a brief review of the common assumptions about biological learning with findings from experimental neuroscience and contrast them with the efficiency of gradient-based learning in recurrent neural networks.
Cortico-cerebellar networks as decoupled neural interfaces
Deep learning methods suffer from similar locking constraints both on the forward and backward phase.
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