305 citations · 611 across the 20 of their papers we have counts for
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Should Under-parameterized Student Networks Copy or Average Teacher Weights?
Berfin Şimşek, Amire Bendjeddou, Wulfram Gerstner +1
Any continuous function can be approximated arbitrarily well by a neural network with sufficiently many neurons . We consider the case when itself is a neural networ…
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…
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…
MLPGradientFlow: going with the flow of multilayer perceptrons (and finding minima fast and accurately)
Johanni Brea, Flavio Martinelli, Berfin Şimşek +1
MLPGradientFlow is a software package to solve numerically the gradient flow differential equation , where are the parameters of a mu…