Stefan M. Wild
Statistics and Probability · 2009–2014
A researcher in the Science corpus: 7 papers; trusts 25 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 28 citations into it
- Artificial Intelligence — 24 citations into it; #14,028 of 35,345 by trust here, #22,463 by citations
- Computational Theory and Mathematics — 20 citations into it; #2,770 of 12,182 by trust here, #5,239 by citations
- Management Science and Operations Research — 15 citations into it
- Numerical Analysis — 11 citations into it; #1,136 of 3,586 by trust here, #1,743 by citations
- Control and Systems Engineering — 7 citations into it
- Environmental Engineering — 6 citations into it
- Aerospace Engineering — 5 citations into it
Whom Stefan M. Wild trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- M. Powell
- Andrea Saltelli
- Anthony OʼHagan
- Jeremy E. Oakley
- M. Montaz Ali
- Leonardo S. Bastos
- Hugh A. Chipman
Who trusts Stefan M. Wild overall
- Rohollah Garmanjani
- Fang He
- Satyajith Amaran
- Charles Audet
- Luís Nunes Vicente
- Nils Reimers
- Nikolaos V. Sahinidis
- T. Nickson
Papers from Stefan M. Wild's perspective
Ordered by how strongly the researchers Stefan M. Wild trusts endorse each paper. Same corpus, a different order for every researcher.
- Bayesian Treed Gaussian Process Models With an Application to Computer Modeling
- Probabilistic sensitivity analysis of complex models: a Bayesian approach
- Genetic Algorithms in Search Optimization and Machine Learning
- A Framework for Validation of Computer Models (Technometrics)
- Efficient Emulators for Multivariate Deterministic Functions
- On the Relative Importance of Input Factors in Mathematical Models
- Global versus local search in constrained optimization of computer models
- Computational approaches to motor learning by imitation.
- Spatial modelling using a new class of nonstationary covariance functions (Environmetrics)
- Making best use of model evaluations to compute sensitivity indices
Their papers
- Modeling an augmented Lagrangian for improved blackbox constrained optimization (2014) — 11 citations
- Variable selection and sensitivity analysis using dynamic trees, with an application to computer code performance tuning (2011) — 37 citations
- Benchmarking Derivative-Free Optimization Algorithms (2009) — 700 citations
- A Bayesian approach for parameter estimation and prediction using a computationally intensive model (2014) — 60 citations
- Nuclear energy density optimization: Shell structure (2013) — 141 citations
- Nuclear energy density optimization: Large deformations (2011) — 285 citations
- Nuclear Energy Density Optimization (2010) — 335 citations