1 citations · 1 across the 4 of their papers we have counts for
4 papers
Two-shot learning of multiple strange attractors
Daniel Köglmayr, Miralem Spahic, Andrew Flynn +1
The brain combines short- and long-term memory to process, store, and recall multiple different pieces of information. Inspired by this and recent results on multifunctional and pa…
Controlling Dynamical Systems into Unseen Target States Using Machine Learning
Daniel Köglmayr, Alexander Haluszczynski, Christoph Räth
We present a novel, model-free, and data-driven methodology for controlling complex dynamical systems into previously unseen target states, including those with significantly diffe…
Controlling dynamical systems to complex target states using machine learning: next-generation vs. classical reservoir computing
Alexander Haluszczynski, Daniel Köglmayr, Christoph Räth
Controlling nonlinear dynamical systems using machine learning allows to not only drive systems into simple behavior like periodicity but also to more complex arbitrary dynamics. F…
Exploring the limits of multifunctionality across different reservoir computers
Andrew Flynn, Oliver Heilmann, Daniel Köglmayr +3
Multifunctional neural networks are capable of performing more than one task without changing any network connections. In this paper we explore the performance of a continuous-time…