Deep Bayesian Approaches for Interpretable Nonlinear Structural System Identification
arXiv:2610.36633v1 Announce Type: cross Abstract: System identification, namely the inference of mathematical representations of dynamical systems from measured data, is fundamental to engineering diagnostics, prognostics, and decision-making. Bayesian filtering offers a principled framework for pr…
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- 2026-10-28 04:00 · arXiv stat.ML
Deep Bayesian Approaches for Interpretable Nonlinear Structural System Identification