Qing-Yu Han

Data-Driven Discovery of High-Dimensional Dynamical Systems with Sparse Interpretable Neural Networks

Existing approaches to explicit data-driven discovery of nonlinear dynamical systems face a curse of dimensionality because candidate libraries grow combinatorially with system dimension. This challenge is particularly severe for high-dimensional systems arising from spatially discretized fields and large complex netwo...