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cs.LG2024
Adaptive control of recurrent neural networks using conceptors
Guillaume Pourcel, Mirko Goldmann, Ingo Fischer +1
Recurrent Neural Networks excel at predicting and generating complex high-dimensional temporal patterns. Due to their inherent nonlinear dynamics and memory, they can learn unbound…
cs.LG2021
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…