24 citations · 27 across the 3 of their papers we have counts for
3 papers
cs.LG2024
BP(λ): Online Learning via Synthetic Gradients
Joseph Pemberton, Rui Ponte Costa
Training recurrent neural networks typically relies on backpropagation through time (BPTT). BPTT depends on forward and backward passes to be completed, rendering the network locke…
q-bio.NC2022★ 24 cited
Single-phase deep learning in cortico-cortical networks
Will Greedy, Heng Wei Zhu, Joseph Pemberton +2
The error-backpropagation (backprop) algorithm remains the most common solution to the credit assignment problem in artificial neural networks. In neuroscience, it is unclear wheth…
q-bio.NC2021★ 3 cited
Current State and Future Directions for Learning in Biological Recurrent Neural Networks: A Perspective Piece
Luke Y. Prince, Roy Henha Eyono, Ellen Boven +9
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 l…