Probabilistic surrogate modeling by Gaussian process: A review on recent insights in estimation and validation
A Marrel, B Iooss - Reliability Engineering & System Safety, 2024 - Elsevier
In the framework of risk assessment, computer codes are increasingly used to understand,
model and predict physical phenomena. As these codes can be very time-consuming to run …
model and predict physical phenomena. As these codes can be very time-consuming to run …
Mechanical behavior predictions of additively manufactured microstructures using functional Gaussian process surrogates
Relational linkages connecting process, structure, and properties are some of the most
sought after goals in additive manufacturing (AM). This is desired especially because the …
sought after goals in additive manufacturing (AM). This is desired especially because the …
Adaptive multi-fidelity Monte Carlo for real-time probabilistic storm surge predictions
Real-time, probabilistic predictions of the expected storm surge represent an important
information source for guiding emergency response decisions during landfalling tropical …
information source for guiding emergency response decisions during landfalling tropical …
Multioutput Gaussian processes with functional data: A study on coastal flood hazard assessment
Surrogate models are often used to replace costly-to-evaluate complex coastal codes to
achieve substantial computational savings. In many of those models, the …
achieve substantial computational savings. In many of those models, the …
A decision-making framework integrating fluid and solid systems to assess resilience of coastal communities experiencing extreme storm events
The precise assessment of flood damage and structural resiliency is of the utmost
importance for coastal communities, mitigating risk from repeated extreme storm events …
importance for coastal communities, mitigating risk from repeated extreme storm events …
Probabilistic surrogate modeling by Gaussian process: A new estimation algorithm for more robust prediction
A Marrel, B Iooss - Reliability Engineering & System Safety, 2024 - Elsevier
In reliability engineering studies, computer codes are increasingly used to model physical
phenomena which, in many cases, can be very time-consuming to run. A widely accepted …
phenomena which, in many cases, can be very time-consuming to run. A widely accepted …
Global sensitivity analysis and Wasserstein spaces
JC Fort, T Klein, A Lagnoux - SIAM/ASA Journal on Uncertainty Quantification, 2021 - SIAM
Sensitivity indices are commonly used to quantify the relative influence of any specific group
of input variables on the output of a computer code. In this paper, we focus both on computer …
of input variables on the output of a computer code. In this paper, we focus both on computer …
Coastal Flood at Gâvres (Brittany, France): A Simulated Dataset to Support Risk Management and Metamodels Development
Given recent scientific advances, coastal flooding events can be modelled even in complex
environments. However, such models are computationally expensive, preventing their use …
environments. However, such models are computationally expensive, preventing their use …
Forecasting of compound ocean-fluvial floods using machine learning
Flood modelling and forecasting can enhance our understanding of flood mechanisms and
facilitate effective management of flood risk. Conventional flood hazard and risk …
facilitate effective management of flood risk. Conventional flood hazard and risk …
A user-oriented local coastal flooding early warning system using metamodelling techniques
Given recent scientific advances, coastal flooding events can be properly modelled.
Nevertheless, such models are computationally expensive (requiring many hours), which …
Nevertheless, such models are computationally expensive (requiring many hours), which …