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Warming up recurrent neural networks to maximise reachable multistability greatly improves learning.
Autor:
Lambrechts G; Montefiore Institute, University of Liège, 10 allée de la découverte, Liège, 4000, Belgium. Electronic address: gaspard.lambrechts@uliege.be., De Geeter F; Montefiore Institute, University of Liège, 10 allée de la découverte, Liège, 4000, Belgium. Electronic address: florent.degeeter@uliege.be., Vecoven N; Montefiore Institute, University of Liège, 10 allée de la découverte, Liège, 4000, Belgium., Ernst D; Montefiore Institute, University of Liège, 10 allée de la découverte, Liège, 4000, Belgium; LTCI, Telecom Paris, Institut Polytechnique de Paris, 19 place Marguerite Perey, Palaiseau, 91120, France. Electronic address: dernst@uliege.be., Drion G; Montefiore Institute, University of Liège, 10 allée de la découverte, Liège, 4000, Belgium. Electronic address: gdrion@uliege.be.
Publikováno v:
Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2023 Sep; Vol. 166, pp. 645-669. Date of Electronic Publication: 2023 Aug 07.