activity
20102026
most citedSubspace dynamic mode decomposition for stochastic Koopman analysis

101 citations · 312 across the 33 of their papers we have counts for

collaborators

36 papers

cs.GT2026

Priority Coordination Games: Hodge Decomposition and a Sharp Design Limit

Zhihao Lin, Jianglin Lan, Anh-Tu Nguyen +1

In decentralised priority coordination, agents announce priority levels and a shared resource serves them in decreasing order, as at an unsignalised intersection; the levels form t…

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…

math.DS2025

Generalized Stochastic Resilience for Early Warning Signals Based on Koopman Operator

Yuta Miyauchi, Masahiro Ikeda, Yoshinobu Kawahara

Developing methods for detecting tipping phenomena at an early stage is an important problem in various fields such as ecology, medicine, and economics. A tipping phenomenon is cha…

math.DS2024★ 4 cited

Koopman operators with intrinsic observables in rigged reproducing kernel Hilbert spaces

Isao Ishikawa, Yuka Hashimoto, Masahiro Ikeda +1

This paper presents a novel approach for estimating the Koopman operator defined on a reproducing kernel Hilbert space (RKHS) and its spectra. We propose an estimation method, what…

nlin.CG2023

Dynamic mode decomposition for Koopman spectral analysis of elementary cellular automata

Keisuke Taga, Yuzuru Kato, Yoshihiro Yamazaki +2

We apply Dynamic Mode Decomposition (DMD) to Elementary Cellular Automata (ECA). Three types of DMD methods are considered and the reproducibility of the system dynamics and Koopma…

stat.ML2022

Modeling Nonlinear Dynamics in Continuous Time with Inductive Biases on Decay Rates and/or Frequencies

Tomoharu Iwata, Yoshinobu Kawahara

We propose a neural network-based model for nonlinear dynamics in continuous time that can impose inductive biases on decay rates and/or frequencies. Inductive biases are helpful f…