A Bayesian sparse identification framework using model averaging recovers interaction structures in dynamical systems with quantified uncertainty in term inclusion.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Amortized neural posterior estimation via simulation-based inference delivers 82x faster inference than MCMC for heat exchanger fouling and leakage diagnosis while maintaining comparable accuracy on synthetic data.
citing papers explorer
-
Uncertainty-Aware Sparse Identification of Dynamical Systems via Bayesian Model Averaging
A Bayesian sparse identification framework using model averaging recovers interaction structures in dynamical systems with quantified uncertainty in term inclusion.
-
Fast Bayesian equipment condition monitoring via simulation based inference: applications to heat exchanger health
Amortized neural posterior estimation via simulation-based inference delivers 82x faster inference than MCMC for heat exchanger fouling and leakage diagnosis while maintaining comparable accuracy on synthetic data.