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Found 4 papers, 2 papers with code
BP(λ): Online Learning via Synthetic Gradients
Inspired by the accumulate $\mathrm{TD}(\lambda)$ in RL, we propose a fully online method for learning synthetic gradients which avoids the use of BPTT altogether: accumulate $BP(\lambda)$.
Single-phase deep learning in cortico-cortical networks
First, we demonstrate that our model can effectively backpropagate errors through multiple layers using a single-phase learning process.
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.
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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