Bayesian inference of earthquake parameters from buoy data using a polynomial chaos-based surrogate

DOI10.1007/s10596-017-9646-zzbMath1369.86007OpenAlexW2605249864MaRDI QIDQ2398875

Omar M. Knio, Kyle T. Mandli, Clint N. Dawson, Ibrahim Hoteit, Olivier P. Le Maître, Loïc Giraldi

Publication date: 21 August 2017

Published in: Computational Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10596-017-9646-z

zbMATH Keywords

shallow water equationBayesian inferencelow-rank representationuncertainty quantificationpolynomial chaos expansionnoise modeltsunamiearthquake inversion

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Seismology (including tsunami modeling), earthquakes (86A15)

Related Items (12)

Uncertainties in the 2004 Sumatra–Andaman source through nonlinear stochastic inversion of tsunami waves ⋮ Optimal projection of observations in a Bayesian setting ⋮ Deep Neural Network Surrogates for Nonsmooth Quantities of Interest in Shape Uncertainty Quantification ⋮ A polynomial chaos framework for probabilistic predictions of storm surge events ⋮ Moment-based invariants for probabilistic loops with non-polynomial assignments ⋮ Probabilistic-learning-based stochastic surrogate model from small incomplete datasets for nonlinear dynamical systems ⋮ Multi-level emulation of tsunami simulations over Cilacap, South Java, Indonesia ⋮ A low-rank solver for parameter estimation and uncertainty quantification in time-dependent systems of partial differential equations ⋮ Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset ⋮ Intrusive generalized polynomial chaos with asynchronous time integration for the solution of the unsteady Navier-Stokes equations ⋮ Combining ensemble Kalman filter and multiresolution analysis for efficient assimilation into adaptive mesh models ⋮ Polynomial surrogates for Bayesian traveltime tomography

Uses Software

• SciPy
• ADCIRC
• GEOCLAW

Cites Work

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