76 citations · 109 across the 3 of their papers we have counts for
3 papers
cs.ET2019
Fast learning synapses with molecular spin valves via selective magnetic potentiation
Alberto Riminucci, Robert Legenstein
We studied LSMO/Alq3/AlOx/Co molecular spin valves in view of their use as synapses in neuromorphic computing. In neuromorphic computing, the learning ability is embodied in specif…
cs.NE2019★ 33 cited
Efficient Reward-Based Structural Plasticity on a SpiNNaker 2 Prototype
Yexin Yan, David Kappel, Felix Neumaerker +7
Advances in neuroscience uncover the mechanisms employed by the brain to efficiently solve complex learning tasks with very limited resources. However, the efficiency is often lost…
cs.NE2019★ 76 cited
Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets
Guillaume Bellec, Franz Scherr, Elias Hajek +3
The way how recurrently connected networks of spiking neurons in the brain acquire powerful information processing capabilities through learning has remained a mystery. This lack o…