Topic-Contributed Paper Session

Modern Perspectives on Statistical Learning for Uncertainty Quantification

Wed, Aug 6, 8:30 AM - 10:20 AM Room CC-202A Music City Center

Ozge SurerOrganizerMoses ChanOrganizerOzge SurerChair

Uncertainty Quantification in Complex Systems Interest Group co: Section on Physical and Engineering Sciencesco: Quality and Productivity Section Applied

5 Presentations

Diffusion Non-Additive Emulator for Multi-Fidelity Computer Experiments with Tuning Parameters

8:30 AM - 10:20 AM

Junoh Heo (Michigan State University)

Co-authors: Junoh Heo (Michigan State University), Romain Boutelet, Chih-Li Sung (Michigan State University)

surrogate model finite-element simulation multi-fidelity

Efficient Active Learning Strategies for Computer Experiments

8:30 AM - 10:20 AM

Difan Song

Co-authors: Roshan Joseph (School of ISYE, Georgia Tech)

Bayesian optimization Gaussian process Screening design Sequential design Surrogate modeling

Global and local validation of computer experiments

8:30 AM - 10:20 AM

Rui Tuo (Texas A&M University)

Computer experiments Uncertainty quantification Multiple testing Kernel ridge regression

MaLT: Machine-Learning-Guided Test Case Design and Fault Localization of Complex Software Systems

8:30 AM - 10:20 AM

Yi (Irene) Ji (JMP)

Co-authors: Yi (Irene) Ji (JMP), Simon Mak, Ryan Lekivetz (JMP), Joseph Morgan (JMP Statistical Discovery LLC)

Fault localization Bayesian modeling Combinatorial testing Active learning Probabilistic machine learning

Strata Design for Variance Reduction in Stochastic Simulation

8:30 AM - 10:20 AM

Jaeshin Park

variance reduction uncertainty quantification stochastic simulation decision-tree