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nlin.CD2026
Ordinal-pattern transition networks as a symbolic substrate for reservoir computing
Max Potratzki, Thomas G. de Jong, Michael Small +1
Reservoir computing has established itself as a computationally efficient alternative to fully trained recurrent neural networks using a fixed high-dimensional nonlinear substrate…
nlin.CD2025
Designing learning in high dimensional oscillator networks with low dimensional read-out
Thomas Geert de Jong
In this paper we investigate a oscillator network based reservoir computer with a large number of oscillators and a low dimensional read-out. The read-out is a function on the aver…