Intrinsic modeling of stochastic dynamical systems using empirical geometry

DOI10.1016/j.acha.2014.08.006zbMath1345.94023OpenAlexW2023717942MaRDI QIDQ2347900

Ronen Talmon, Ronald R. Coifman

Publication date: 10 June 2015

Published in: Applied and Computational Harmonic Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.acha.2014.08.006

zbMATH Keywords

differential geometrynonlinear dynamical systemsinformation geometrymanifold learningnonlinear inverse problemnon-parametric estimationintrinsic modelgraph-based method

Mathematics Subject Classification ID

Information theory (general) (94A15) Reliability and life testing (62N05)

Related Items (5)

Data-Driven Reduction for a Class of Multiscale Fast-Slow Stochastic Dynamical Systems ⋮ Multi-view kernel consensus for data analysis ⋮ Polynomial chaos representation of databases on manifolds ⋮ Parsimonious representation of nonlinear dynamical systems through manifold learning: a chemotaxis case study ⋮ Data-driven probability concentration and sampling on manifold

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