6 citations · 8 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 6 cited
Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems
Manuel Brenner, Florian Hess, Jonas M. Mikhaeil +4
In many scientific disciplines, we are interested in inferring the nonlinear dynamical system underlying a set of observed time series, a challenging task in the face of chaotic be…
cs.LG2022★ 2 cited
Continual Learning of Dynamical Systems with Competitive Federated Reservoir Computing
Leonard Bereska, Efstratios Gavves
Machine learning recently proved efficient in learning differential equations and dynamical systems from data. However, the data is commonly assumed to originate from a single neve…