Bayesian non-parametric approaches to reconstructing oscillatory systems and the Nyquist limit

DOI10.1016/j.physa.2014.03.069zbMath1395.62072OpenAlexW2070589046MaRDI QIDQ1782875

Justina Žurauskienė, Thomas Thorne, Michael P. H. Stumpf, Paul D. W. Kirk

Publication date: 20 September 2018

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://www.pure.ed.ac.uk/ws/files/20039172/Nonparametrics_Nyquist_Limit_physicaA.pdf

zbMATH Keywords

Gaussian processesNyquist limitoscillating systemsmultiple-output Gaussian processes

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Bayesian inference (62F15) Applications of statistics to physics (62P35)

Related Items (1)

Collocation based training of neural ordinary differential equations

Uses Software

• BayesDA

Cites Work

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• Gaussian processes for time-series modelling
• Bayesian non-parametrics and the probabilistic approach to modelling
• Confidence bands for inverse regression models
• Inverse problems in systems biology
• Inverse Problem Theory and Methods for Model Parameter Estimation
• FM demodulation in the presence of multiplicative and additive noise
• A Simplex Method for Function Minimization

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