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Modeling the Dynamics of PDE Systems with Physics-Constrained Deep Auto-Regressive Networks., and . CoRR, (2019)Sparse grid collocation schemes for stochastic natural convection problems., and . J. Comput. Phys., 225 (1): 652-685 (2007)A stochastic multiscale framework for modeling flow through random heterogeneous porous media., and . J. Comput. Phys., 228 (2): 591-618 (2009)A non-linear dimension reduction methodology for generating data-driven stochastic input models., and . J. Comput. Phys., 227 (13): 6612-6637 (2008)Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification., and . J. Comput. Phys., (2018)Structured Bayesian Gaussian process latent variable model: applications to data-driven dimensionality reduction and high-dimensional inversion., and . CoRR, (2018)Multidimensional Adaptive Relevance Vector Machines for Uncertainty Quantification., and . SIAM J. Sci. Comput., (2012)Multi-fidelity Generative Deep Learning Turbulent Flows., and . CoRR, (2020)Embedded-physics machine learning for coarse-graining and collective variable discovery without data., , and . CoRR, (2020)Kernel principal component analysis for stochastic input model generation., and . J. Comput. Phys., 230 (19): 7311-7331 (2011)