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Quantifying Sampling Noise and Parametric Uncertainty in Atomistic-to-Continuum Simulations Using Surrogate Models., , , , and . Multiscale Model. Simul., 13 (3): 953-976 (2015)Trigger Detection for Adaptive Scientific Workflows Using Percentile Sampling., , , , , and . SIAM J. Sci. Comput., (2016)Optimal Compressed Sensing and Reconstruction of Unstructured Mesh Datasets., , , , , , , , , and . Data Sci. Eng., 3 (1): 1-23 (2018)Uncertainty Quantification in MD Simulations. Part II: Bayesian Inference of Force-Field Parameters., , , , , , and . Multiscale Modeling & Simulation, 10 (4): 1460-1492 (2012)Compressed Sensing and Reconstruction of Unstructured Mesh Datasets., , , and . CoRR, (2015)A Stochastic Multiscale Coupling Scheme to Account for Sampling Noise in Atomistic-to-Continuum Simulations., , , , , and . Multiscale Model. Simul., 10 (2): 550-584 (2012)Robust Digital Computation in the Physical World., , , , and . Cyber-Physical Systems Security, Springer, (2018)Multi-scale study of nanoparticle transport and deposition in tissues during an injection process., , , and . Medical Biol. Eng. Comput., 48 (9): 853-863 (2010)Bayesian Inference of Atomic Diffusivity in a Binary Ni/Al System Based on Molecular Dynamics., , , , , , , and . Multiscale Model. Simul., 9 (1): 486-512 (2011)Physics-Based Checksums for Silent-Error Detection in PDE Solvers., , and . Euro-Par Workshops, volume 11997 of Lecture Notes in Computer Science, page 681-693. Springer, (2019)