Hoang K. Chu

Discovering Interpretable Dynamics by Sparsity Promotion on Energy and the Lagrangian

Data-driven modeling frameworks that adopt sparse regression techniques, such as sparse identification of nonlinear dynamics (SINDy) and its modifications, are developed to resolve difficulties in extracting underlying dynamics from experimental data. In contrast to neural-network-based methods, the