90 citations · 101 across the 3 of their papers we have counts for
3 papers
q-bio.NC2017★ 6 cited
Non-linear motor control by local learning in spiking neural networks
Aditya Gilra, Wulfram Gerstner
Learning weights in a spiking neural network with hidden neurons, using local, stable and online rules, to control non-linear body dynamics is an open problem. Here, we employ a su…
q-bio.NC2017★ 5 cited
Multi-timescale memory dynamics in a reinforcement learning network with attention-gated memory
Marco Martinolli, Wulfram Gerstner, Aditya Gilra
Learning and memory are intertwined in our brain and their relationship is at the core of several recent neural network models. In particular, the Attention-Gated MEmory Tagging mo…
q-bio.NC2017★ 90 cited
Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network
Aditya Gilra, Wulfram Gerstner
Brains need to predict how the body reacts to motor commands. It is an open question how networks of spiking neurons can learn to reproduce the non-linear body dynamics caused by m…