January 01, 2013 book Uncertainty Quantification: Theory, Implementation, and Applications Society for Industrial and Applied Mathematics eBooks DOI: 10.1137/1.9781611973228 OpenAlex Authors 0 Author list not loaded yet. Cited by 6 stored of 1,179 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Entropy-conservative high-order methods for high-enthalpy gas flows 2025 Computers & Fluids article Engineering Computational Fluid Dynamics and Aerodynamics Open access 1 citations Model Credibility 2024 Synthesis lectures on biomedical engineering book-chapter Decision Sciences Simulation Techniques and Applications Open access 7 citations First detection of collective oscillations of a stored deuteron beam with an amplitude close to the quantum limit 2021 Physical Review Accelerators and Beams article Engineering Particle accelerators and beam dynamics Open access 12 citations Uncertainty quantification of offshore wind farms using Monte Carlo and sparse grid 2021 Energy Sources Part B Economics Planning and Policy article Engineering Wind Energy Research and Development 8 citations Global Sensitivity Analysis for Patient-Specific Aortic Simulations: The Role of Geometry, Boundary Condition and Large Eddy Simulation Modeling Parameters 2020 Journal of Biomechanical Engineering article Decision Sciences Probabilistic and Robust Engineering Design 18 citations Spectral methods to study the robustness of residual neural networks with infinite layers 2020 Foundations of Data Science article Physics and Astronomy Model Reduction and Neural Networks Open access 4 citations 6 results References 0