Data-driven sparse identification of governing PDEs via knockoff filters and multi-criteria trade-offs

Pongpisit Thanasutives, Naichang Ke, Yoshinobu Kawahara

We propose KO-PDE-IDENT, a data-driven framework for identifying parsimonious partial differential equations (PDEs) with false discovery rate (FDR) control. PDE discovery from nois…