407 citations · 1.4k across the 17 of their papers we have counts for
18 papers
Experimental demonstration of bandwidth enhancement in photonic time delay reservoir computing
Irene Estebanez, Apostolos Argyris, Ingo Fischer
Time delay reservoir computing (TDRC) using semiconductor lasers (SLs) has proven to be a promising photonic analog approach for information processing. One appealing property is t…
Injection locking and coupling the emitters of large VCSEL arrays via diffraction in an external cavity
Moritz Pflüger, Daniel Brunner, Tobias Heuser +3
Networks of optically coupled semiconductor lasers are of high interest for fundamental investigations and for enabling numerous technological applications in material processing,…
Learning unseen coexisting attractors
Daniel J. Gauthier, Ingo Fischer, André Röhm
Reservoir computing is a machine learning approach that can generate a surrogate model of a dynamical system. It can learn the underlying dynamical system using fewer trainable par…
Tutorial: Photonic Neural Networks in Delay Systems
D. Brunner, B. Penkovsky, B. A. Marquez +3
Photonic delay systems have revolutionized the hardware implementation of Recurrent Neural Networks and Reservoir Computing in particular. The fundamental principles of Reservoir C…
Learn one size to infer all: Exploiting translational symmetries in delay-dynamical and spatio-temporal systems using scalable neural networks
Mirko Goldmann, Claudio R. Mirasso, Ingo Fischer +1
We design scalable neural networks adapted to translational symmetries in dynamical systems, capable of inferring untrained high-dimensional dynamics for different system sizes. We…
Model-free inference of unseen attractors: Reconstructing phase space features from a single noisy trajectory using reservoir computing
André Röhm, Daniel J. Gauthier, Ingo Fischer
Reservoir computers are powerful tools for chaotic time series prediction. They can be trained to approximate phase space flows and can thus both predict future values to a high ac…