3 papers
stat.AP2026
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…
cs.LG2026
Structured Noise Adaptation for Sequential Bayesian Filtering with Embedded Latent Transfer Operators
Naichang Ke, Pongpisit Thanasutives, Yoshinobu Kawahara
Kalman filters based on the Embedded Latent Transfer Operators (ELTO) emerge as novel statistical tools for sequential state estimation. However, a critical limitation stems from t…
cs.LG2025
Learning Stochastic Nonlinear Dynamics with Embedded Latent Transfer Operators
Naichang Ke, Ryogo Tanaka, Yoshinobu Kawahara
We consider an operator-based latent Markov representation of a stochastic nonlinear dynamical system, where the stochastic evolution of the latent state embedded in a reproducing…