ENBIS-26 Conference

Session

Design and modeling of computer experiments

Sep 8, 2026, 2:00 PM

Conveners

Design and modeling of computer experiments

• Bertrand Iooss (EDF R&D)

29. Random Designs for Quantisation in High Dimension

Luc Pronzato (CNRS)

9/8/26, 2:00 PM

Other/special session/invited session

Incremental design for computer experiments traditionally relies on space-filling or uniformity criteria, but these become impractical in high dimensions. The greedy minimisation of the $L_s$-mean quantisation error (or distortion) offers a valuable alternative, though it is also computationally intractable for large $d$.

This talk focuses on random designs composed of i.i.d. points sampled...

16. Active Subspace Embedding for Parsimonious Gaussian Process Surrogates

Amandine MARREL (CEA)

9/8/26, 2:30 PM

Other/special session/invited session

Uncertainty quantification for complex physical systems often relies on computationally expensive numerical simulators. When execution times limit the number of feasible runs, surrogate modeling becomes essential for tasks such as sensitivity analysis, design optimization, and safety assessment. Gaussian process regression (GPR) is a leading
surrogate due to its uncertainty...

74. Multivariate sensitivity analysis for risk analysis with spatial outputs: a comparison exercise

Jérémy ROHMER (BRGM)

9/8/26, 3:00 PM

Other/special session/invited session

Maps play a key role in many applications to facilitate decision-making for risk analysis, such as in assessing natural hazards, soil pollution, water quality, and so on. Performing global sensitivity analysis in a spatial context can benefit from multiple approaches adapted to multivariate outputs, namely: 1. the combination of variance-based sensitivity indices and functional principal...