80 citations · 292 across the 14 of their papers we have counts for
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cs.LG2021★ 9 cited
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series
Daniel Kramer, Philine Lou Bommer, Carlo Tombolini +2
Empirically observed time series in physics, biology, or medicine, are commonly generated by some underlying dynamical system (DS) which is the target of scientific interest. There…
cs.LG2021★ 17 cited
On the difficulty of learning chaotic dynamics with RNNs
Jonas M. Mikhaeil, Zahra Monfared, Daniel Durstewitz
Recurrent neural networks (RNNs) are wide-spread machine learning tools for modeling sequential and time series data. They are notoriously hard to train because their loss gradient…