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Approximate Latent Force Model Inference
[article]
2022
arXiv
pre-print
Physically-inspired latent force models offer an interpretable alternative to purely data driven tools for inference in dynamical systems. They carry the structure of differential equations and the flexibility of Gaussian processes, yielding interpretable parameters and dynamics-imposed latent functions. However, the existing inference techniques associated with these models rely on the exact computation of posterior kernel terms which are seldom available in analytical form. Most applications
arXiv:2109.11851v3
fatcat:fx6tcxwgcbaxznudxshy4ziiba