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Efficient Bayesian calibration of many-parameter system models
Promit Chakroborty, Sankaran Mahadevan
Computer models of complex engineering systems rely on proper tuning of their model parameters to ensure accurate predictions of the system behavior. The challenge of effectively c…
The tail wags the distribution: Only sample the tails for efficient reliability analysis
Promit Chakroborty, Michael D. Shields
To ensure that real-world infrastructure is safe and durable, systems are designed to not fail for any but the most rarely occurring parameter values. By only happening deep in the…
Intrepid MCMC: Metropolis-Hastings with Exploration
Promit Chakroborty, Michael D. Shields
In engineering examples, one often encounters the need to sample from unnormalized distributions with complex shapes that may also be implicitly defined through a physical or numer…
Covariance-free Bi-fidelity Control Variates Importance Sampling for Rare Event Reliability Analysis
Promit Chakroborty, Somayajulu L. N. Dhulipala, Michael D. Shields
Multifidelity modeling has been steadily gaining attention as a tool to address the problem of exorbitant model evaluation costs that makes the estimation of failure probabilities…