Below ocean wind farms, oil rigs and other offshore installations are mammoth networks of underwater structures, including ...

Regression models with intractable normalizing constants are valuable tools for analyzing complex data structures, yet ...

Submarine landslides can hamper the productivity of offshore installations, but researchers at Texas A&M may now be able to ...

Working within the standard single-factor framework, we present two Bayesian approaches to the level validation of a PD model. The first approach provides ... The second approach provides a means for ...

This introduces probabilistic dose adjustments, improving decision making while retaining the model-free and calibration-free nature of CFO ... The flowchart of the Bayesian CFO-type design for phase ...

In our group, Bayesian statistics is largely used to estimate model parameters (Bayesian calibration), to evaluate model performances (Bayesian model comparison), to combine multiple model predictions ...

With the continuous advancement of photoelectric performance in major equipment and advanced instruments, traditional optical elements are ...

A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...