114 citations · 251 across the 9 of their papers we have counts for
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cs.LG2023★ 1 cited
Model scale versus domain knowledge in statistical forecasting of chaotic systems
William Gilpin
Chaos and unpredictability are traditionally synonymous, yet large-scale machine learning methods recently have demonstrated a surprising ability to forecast chaotic systems well b…
cs.LG2021★ 4 cited
Chaos as an interpretable benchmark for forecasting and data-driven modelling
William Gilpin
The striking fractal geometry of strange attractors underscores the generative nature of chaos: like probability distributions, chaotic systems can be repeatedly measured to produc…
cs.LG2020★ 35 cited
Deep reconstruction of strange attractors from time series
William Gilpin
Experimental measurements of physical systems often have a limited number of independent channels, causing essential dynamical variables to remain unobserved. However, many popular…