Multilevel weighted support vector machine for classification on healthcare data with missing values T Razzaghi, O Roderick, I Safro, N Marko PloS one 11 (5), e0155119, 2016 | 92 | 2016 |
Polynomial regression approaches using derivative information for uncertainty quantification O Roderick, M Anitescu, P Fischer Nuclear Science and Engineering 164 (2), 122-139, 2010 | 80 | 2010 |
Orthogonal bases for polynomial regression with derivative information in uncertainty quantification Y Li, M Anitescu, O Roderick, F Hickernell Visualization of Mechanical Processes: An International Online Journal 1 (4), 2011 | 30 | 2011 |
Fast imbalanced classification of healthcare data with missing values T Razzaghi, O Roderick, I Safro, N Marko 2015 18th International Conference on Information Fusion (Fusion), 774-781, 2015 | 21 | 2015 |
Proper orthogonal decompositions in multifidelity uncertainty quantification of complex simulation models O Roderick, M Anitescu, Y Peet International Journal of Computer Mathematics 91 (4), 748-769, 2014 | 16 | 2014 |
Automatic differentiation of codes in nuclear engineering applications. M Alexe, O Roderick, J Utke, M Anitescu, P Hovland, T Fanning Argonne National Lab.(ANL), Argonne, IL (United States), 2009 | 10 | 2009 |
Data analysis and machine learning effort in healthcare: Organization, limitations, and development of an approach O Roderick, N Marko, D Sanchez, A Aryasomajula Internet of Things and Data Analytics Handbook, 295-328, 2017 | 9 | 2017 |
Using automatic differentiation in sensitivity analysis of nuclear simulation models M Alexe, O Roderick, M Anitescu, J Utke, T Fanning, P Hovland Transactions of the American Nuclear Society 102, 235, 2010 | 9 | 2010 |
Stochastic finite element approaches using derivative information for uncertainty quantification O Roderick, M Anitescu, P Fischer Nuclear Science and Engineering 164 (2), 122-139, 2010 | 5 | 2010 |
Stochastic finite-element approach in nuclear reactor uncertainty quantification O Roderick, M Anitescu, P Fischer, WS Yang Transactions of American Nuclear Society 100, 317-318, 2009 | 4 | 2009 |
Dimensionality reduction for uncertainty quantification of nuclear engineering models O Roderick, Z Wang, M Anitescu Science and Engineering 164 (2), 122-138, 2010 | 2 | 2010 |
Learning of highly-filtered data manifold using spectral methods O Roderick, I Safro International Conference on Learning and Intelligent Optimization, 154-168, 2010 | 1 | 2010 |
Model reduction for simulation, optimization and control OE Roderick Portland State University, 2009 | 1 | 2009 |
Intrusive analysis for NEK5000: development of intrusive uncertainty quantification for high-dimensional, high-fidelity codes. O Roderick, M Anitescu Argonne National Lab.(ANL), Argonne, IL (United States), 2012 | | 2012 |
Derivative-based uncertainty quantification: automatic differentiation tools for SAS. O Roderick, M Anitescu, J Utke Argonne National Lab.(ANL), Argonne, IL (United States), 2012 | | 2012 |
Reduced Order Approximations in Uncertainty Analysis of Nuclear Engineering Applications O Roderick, M Anitescu, Z Wang Transactions of the American Nuclear Society 106, 437-438, 2012 | | 2012 |
Sensitivity and Uncertainty Methodologies in Nuclear Calculations—I-Dimensionality Reduction for Uncertainty Quantification of Nuclear Engineering Models O Roderick, Z Wang, M Anitescu Transactions of the American Nuclear Society 104, 339, 2011 | | 2011 |
Polynomial Regression with Derivative Information for Uncertainty Analysis of Complex Simulation Models. O Roderick, M Anitescu, Y Li, Z Wang | | 2010 |
High-Order Interpolation for Predicting Decisions and Recovering Missing Data O Roderick, I Safro | | 2010 |
Polynomial regression with derivative information in nuclear reactor uncertainty quantification M Anitescua, O Rodericka, P Fischera, WS Yangb | | 2009 |