3 papers
cond-mat.dis-nn2020
Unfolding recurrence by Green's functions for optimized reservoir computing
Sandra Nestler, Christian Keup, David Dahmen +3
Cortical networks are strongly recurrent, and neurons have intrinsic temporal dynamics. This sets them apart from deep feed-forward networks. Despite the tremendous progress in the…
cond-mat.dis-nn2019
Capacity of the covariance perceptron
David Dahmen, Matthieu Gilson, Moritz Helias
The classical perceptron is a simple neural network that performs a binary classification by a linear mapping between static inputs and outputs and application of a threshold. For…
cond-mat.dis-nn2016
Functional methods for disordered neural networks
Jannis Schuecker, Sven Goedeke, David Dahmen +1
Neural networks of the brain form one of the most complex systems we know. Many qualitative features of the emerging collective phenomena, such as correlated activity, stability, r…