Kriging-based adaptive Importance Sampling algorithms for rare event estimation

By M. Balesdent, J. Morio, J. Marzat. 2013

160 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/a003f553930c87ea978476dd85719198dbfa8b98

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Bruno Sudret
2. Stefano Marelli
3. Maliki Moustapha

In Statistics and Probability

1. Stefano Marelli
2. Bruno Sudret
3. Maliki Moustapha
4. Anthony Nouy
5. Xiaoping Du
6. Zhen Hu
7. Géraud Blatman
8. Wolfgang Nowak

Citations in the corpus

• LIF: A new Kriging based learning function and its application to structural reliability analysis (2017, unknown): “This two-dimension analytical example already analyzed in [9,34,49] consists of a modified Rastrigin function.”
• Active learning for structural reliability: Survey, general framework and benchmark (2021, background): “For instance, Balesdent et al. (2013) sequentially built and enriched Kriging models”