4 papers · 1 filter
Emergent rate-based dynamics in duplicate-free populations of spiking neurons
Valentin Schmutz, Johanni Brea, Wulfram Gerstner
Can Spiking Neural Networks (SNNs) approximate the dynamics of Recurrent Neural Networks (RNNs)? Arguments in classical mean-field theory based on laws of large numbers provide a p…
Kernel Memory Networks: A Unifying Framework for Memory Modeling
Georgios Iatropoulos, Johanni Brea, Wulfram Gerstner
We consider the problem of training a neural network to store a set of patterns with maximal noise robustness. A solution, in terms of optimal weights and state update rules, is de…
Expand-and-Cluster: Parameter Recovery of Neural Networks
Flavio Martinelli, Berfin Simsek, Wulfram Gerstner +1
Can we identify the weights of a neural network by probing its input-output mapping? At first glance, this problem seems to have many solutions because of permutation, overparamete…
Context selectivity with dynamic availability enables lifelong continual learning
Martin Barry, Wulfram Gerstner, Guillaume Bellec
"You never forget how to ride a bike", -- but how is that possible? The brain is able to learn complex skills, stop the practice for years, learn other skills in between, and still…