Julien Bect
Statistics and Probability · 2007–2011
A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 19 citations into it
- Computational Theory and Mathematics — 14 citations into it; #3,472 of 12,182 by trust here, #3,681 by citations
- Management Science and Operations Research — 14 citations into it
- Artificial Intelligence — 10 citations into it; #12,362 of 35,345 by trust here, #21,316 by citations
- Mathematical Optimization — 7 citations into it
Whom Julien Bect trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Anthony OʼHagan
- Jeremy E. Oakley
- Donald R. Jones
- Jonas Mockus
- Harold J. Kushner
- Michael L. Stein
- Michael A. Osborne
- Ilya S. Molchanov
- Reuven Y. Rubinstein
- Michael E. Hohn
Who trusts Julien Bect overall
Papers from Julien Bect's perspective
Ordered by how strongly the researchers Julien Bect trusts endorse each paper. Same corpus, a different order for every researcher.
- Design and analysis of computer experiments
- Efficient Global Optimization of Expensive Black-Box Functions
- A New Method of Locating the Maximum Point of an Arbitrary Multipeak Curve in the Presence of Noise
- A Framework for Validation of Computer Models (Technometrics)
- A Taxonomy of Global Optimization Methods Based on Response Surfaces
- Interpolation of spatial data
- Probabilistic sensitivity analysis of complex models: a Bayesian approach
- A Correspondence Between Bayesian Estimation on Stochastic Processes and Smoothing by Splines
- Bayesian inference for the uncertainty distribution of computer model outputs
- Kriging is well-suited to parallelize optimization
Their papers
- Robust Gaussian Process-Based Global Optimization Using a Fully Bayesian Expected Improvement Criterion (2011) — 77 citations
- Convergence properties of the expected improvement algorithm with fixed mean and covariance functions (2007) — 252 citations
- Sequential design of computer experiments for the estimation of a probability of failure (2010) — 386 citations