output
20042021
most citedThe synthesis of data from instrumented structures and physics-based models via Gaussian processes

17 citations

5 papers

stat.ME2021★ 17 cited

Low-rank statistical finite elements for scalable model-data synthesis

Connor Duffin, Edward Cripps, Thomas Stemler +1

Statistical learning additions to physically derived mathematical models are gaining traction in the literature. A recent approach has been to augment the underlying physics of the…

cs.CE2020★ 5 cited

Various Ways to Quantify BDMPs

Marc Bouissou, Shahid Khan, Joost-Pieter Katoen +1

A Boolean logic driven Markov process (BDMP) is a dependability analysis model that defines a continuous-time Markov chain (CTMC). This formalism has high expressive power, yet it…

stat.AP2018★ 17 cited

The synthesis of data from instrumented structures and physics-based models via Gaussian processes

Alastair Gregory, Din-Houn Lau, Mark Girolami +2

A recent development which is poised to disrupt current structural engineering practice is the use of data obtained from physical structures such as bridges, viaducts and buildings…

stat.ME2018

Generalized Log-Normal Chain-Ladder

D. Kuang, B. Nielsen

We propose an asymptotic theory for distribution forecasting from the log normal chain-ladder model. The theory overcomes the difficulty of convoluting log normal variables and tak…

cond-mat.other2004

Estimating Probabilities of Default for Low Default Portfolios

Katja Pluto, Dirk Tasche

For credit risk management purposes in general, and for allocation of regulatory capital by banks in particular (Basel II), numerical assessments of the credit-worthiness of borrow…