Paul G. Constantine
Statistics and Probability · 2008–2017
A researcher in the Science corpus: 5 papers; trusts 31 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 53 citations into it; #4,334 of 12,932 by trust here, #3,513 by citations
- Computational Theory and Mathematics — 28 citations into it; #2,806 of 12,182 by trust here, #3,448 by citations
- Computational Mechanics — 21 citations into it
- Statistical and Nonlinear Physics — 19 citations into it; #3,815 of 10,127 by trust here, #3,616 by citations
- Artificial Intelligence — 11 citations into it
- Civil and Structural Engineering — 10 citations into it; #4,549 of 6,160 by trust here, #4,288 by citations
- Management Science and Operations Research — 9 citations into it; #11,659 of 11,946 by trust here, #8,906 by citations
- Applied Mathematics — 6 citations into it
Whom Paul G. Constantine trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Donald R. Jones
- Andreas Griewank
- Danny C. Sorensen
- Y. Saad
- Boaz Nadler
- Andrea Walther
- B. Kulfan
- Mario Bebendorf
- Nathan Halko
- Arnaud Doucet
Who trusts Paul G. Constantine overall
- Ji-chao Li
- Sharmila Karumuri
- Rohit Tripathy
- Maliki Moustapha
- Constantin Grigo
- Xiaosong Du
- Ilias Bilionis
- Joaquim R. Martins
- Zhongming Jiang
- Stefano Marelli
Papers from Paul G. Constantine's perspective
Ordered by how strongly the researchers Paul G. Constantine trusts endorse each paper. Same corpus, a different order for every researcher.
- Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions
- A Taxonomy of Global Optimization Methods Based on Response Surfaces
- Regression Shrinkage and Selection via the Lasso
- Sequential Monte Carlo Methods in Practice
- Robust and optimal control
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Numerical methods for large eigenvalue problems (Acta Numerica)
- Finite sample approximation results for principal component analysis: a matrix perturbation approach
- ImageNet classification with deep convolutional neural networks
- Numerical Methods for Large Eigenvalue Problems
Their papers
- Active Subspace Methods in Theory and Practice: Applications to Kriging Surfaces (2013) — 621 citations
- Evaluation of Non-Intrusive Approaches for Wiener-Askey Generalized Polynomial Chaos. (2008) — 206 citations
- Active Subspaces for Shape Optimization (2014) — 173 citations
- Active Subspaces - Emerging Ideas for Dimension Reduction in Parameter Studies (2015) — 442 citations
- Active Subspaces of Airfoil Shape Parameterizations (2017) — 60 citations