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<!DOCTYPE html>
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1" >
<meta name="viewport" content="width=device-width,initial-scale=1">
<title>Rocky Mountain Summer Workshop on Uncertainty Quantification</title>
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<div class="content-wrapper">
<h1>Rocky Mountain Summer Workshop on Uncertainty Quantification</h1>
<h2>University of Colorado Denver</h2>
<h3>July 15-17, 2015</h3>
<ul class="top-nav">
<li class="top-nav-list"><a class="nav-link" href="index.html">Home</a></li>
<li class="top-nav-list"><a class="nav-link" href="logistics.html">Logistics</a></li>
<li class="top-nav-list"><a class="nav-link" href="contacts.html">Contacts</a></li>
<!-- <li class="top-nav-list"><a class="nav-link" href="participants.html">Participants</a></li> -->
<li class="top-nav-list"><a class="nav-link" href="program.html">Program</a></li>
<li class="top-nav-list"><a class="nav-link" href="references.html">References</a></li>
<li class="top-nav-list"><a class="nav-link" href="denver.html">Denver</a></li>
<h2>References</h2>
<h3>Bayesian Inverse Problems and QUESO</h3>
<ul>
<li>D. McDougall, Bayesian parameter estimation in predictve engineering,
Institute for Computational Engineering and Sciences, UT Austin, 2014.
<a href="http://users.ices.utexas.edu/~damon/imperial_talk_mcdougall.pdf
">http://users.ices.utexas.edu/~damon/imperial_talk_mcdougall.pdf
</a></li><p>
<li>D. McDougall, N. Malaya, R. D. Moser, The Parallel C++ Statistical Library
for Bayesian Inference: QUESO, 2015.
<a href="http://arxiv.org/abs/1507.00398">http://arxiv.org/abs/1507.00398</a></li><p>
<li>K. C. Estacio-Hiroms, E. E. Prudencio, The QUESO Library User's Manual,
Quantification of Uncertainty for Estimation, Simulation, and Optimization (QUESO),
Version 0.50.0, Center for Predictive Engineering and Computational Sciecnes (PECOS),
Institute for Computational Engineering and Sciences (ICES), 2008-2013.
<a href="https://github.com/libqueso/queso/blob/dev/QUESO_users_manual.pdf
">https://github.com/libqueso/queso/blob/dev/QUESO_users_manual.pdf
</a></li><p>
</ul>
<h3>Bayesian Inverse Problems and Ice Sheet Modeling</h3>
<ul>
<li>T. Isaac, N. Petra, G. Stadler, O. Ghattas, Scalable and efficient
algorithms for the propagation of uncertainty from data through
inference to prediction for large-scale problems, with application to
flow of the Antarctic ice sheet, Journal of Computational Physics,
296(1):348–368, 2015.
<a href="http://dx.doi.org/10.1016/j.jcp.2015.04.047">
http://dx.doi.org/10.1016/j.jcp.2015.04.047</a></li><p>
<li>N. Petra, H. Zhu, G. Stadler, T.J.R. Hughes, O. Ghattas, An inexact
Gauss-Newton method for inversion of basal sliding and rheology
parameters in a nonlinear Stokes ice sheet model, Journal of
Glaciology, 58(211):889–903, 2012.
<a href="http://dx.doi.org/10.3189/2012JoG11J18">
2http://dx.doi.org/10.3189/2012JoG11J182</a></li><p>
<li>T. Bui-Thanh, O. Ghattas, J. Martin, and G. Stadler, A computational
framework for infinite-dimensional Bayesian inverse problems. Part I:
The linearized case, with applications to global seismic inversion.
SIAM Journal on Scientific Computing, 35(6):A2494-A2523, 2013.
<a href="http://dx.doi.org/10.1137/12089586X">http://dx.doi.org/10.1137/12089586X</a></li><p>
<li>N. Petra, J. Martin, G. Stadler, and O. Ghattas, A computational
framework for infinite-dimensional Bayesian inverse problems. Part II:
Stochastic Newton MCMC with application to ice sheet flow inverse
problems, SIAM Journal on Scientific Computing, 36(4):A1525–A1555,
2014.
<a href="http://dx.doi.org/10.1137/130934805">http://dx.doi.org/10.1137/130934805</a></li><p>
</ul>
<h3>Measure-Theoretic Inverse Problems and Applications</h3>
<ul>
<li>T. Bulter, D. Estep, S. Tavener, C. Dawson, J. J. Westerink,
A measure-theoretic computational method for inverse sensitivity problems III:
Multiple quantities of interest. SIAM/ASA Journal on Uncertainty Quantification, 2:1, 174-202.
<a href="http://epubs.siam.org/doi/pdf/10.1137/130930406">
http://epubs.siam.org/doi/pdf/10.1137/130930406</a></li><p>
<li>T. Butler, L. Graham, D. Estep, C. Dawson, J.J. Westerink, Definition and solution of a
stochastic inverse problem for the Manning’s n parameter field in hydrodynamic models,
Advances in Water Resources, Available online 3 February 2015, ISSN 0309-1708,
<a href="http://dx.doi.org/10.1016/j.advwatres.2015.01.011">
doi:10.1016/j.advwatres.2015.01.011</a>.</li><p>
<li>T. Butler, D. Estep, S. Tavener, T. Wildey, C. Dawson, and L. Graham, Solving stochastic inverse
problems using sigma-algebras on contour maps, 2014, <a href="http://arxiv.org/pdf/1407.3851">
arXiv preprint arXiv:1407.3851</a></li><p>
<li>D. R. Harp, V. V. Vesselinov, Contaminant remediation decision analysis using information gap
theory, Stochastic Environmental Research and Risk Assessment, 27, 159-168, 2013.
<a href="http://dx.doi.org/10.1007/s00477-012-0573-1">doi:10.1007/s00477-012-0573-1</a></li><p>
<li>S. Bunya, J. C. Dietrich, J. J. Westerink, B. A. Ebersole, J. M. Smith, J. H. Atkinson,
R. Jensen, D. T. Resio, R. A. Luettich, C. Dawson, V. J. Cardone, A. T. Cox, M. D. Powell,
H. J. Westerink, and H. J. Roberts, 2010: A High-Resolution Coupled Riverine flow, tide, wind,
Wind Wave, and Storm Surge Model for Southern Louisiana and Mississippi. Part I: Model
Development and Validation. Mon. Wea. Rev., 138, 345–377.
<a href="http://journals.ametsoc.org/doi/abs/10.1175/2009MWR2906.1">
doi: http://dx.doi.org/10.1175/2009MWR2906.1</a></li><p>
<li>The Official ADCIRC Web Site <a href="http://adcirc.org/">http://adcirc.org/</a></li><p>
</ul>
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