Nicolas Schunck
Nuclear and High Energy Physics · 2010–2020
A researcher in the Science corpus: 7 papers; trusts 4 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Nuclear and High Energy Physics — 72 citations into it; #5,889 of 6,161 by trust here, #3,560 by citations
- Statistics and Probability — 11 citations into it
- Computational Theory and Mathematics — 6 citations into it
- Management Science and Operations Research — 5 citations into it
Whom Nicolas Schunck trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Nicolas Schunck overall
Papers from Nicolas Schunck's perspective
Ordered by how strongly the researchers Nicolas Schunck trusts endorse each paper. Same corpus, a different order for every researcher.
- Probabilistic sensitivity analysis of complex models: a Bayesian approach
- Computer Model Calibration Using High-Dimensional Output
- A Framework for Validation of Computer Models (Technometrics)
- Influence of cultivation temperature on the ligninolytic activity of selected fungal strains
- Efficient Emulators for Multivariate Deterministic Functions
- Introduction to derivative-free optimization
- Inverse problem theory - and methods for model parameter estimation
- Introduction to Derivative-Free Optimization
- Genetic Algorithms in Search Optimization and Machine Learning
- Applied Statistics and Probability for Engineers (Technometrics)
Their papers
- A Bayesian approach for parameter estimation and prediction using a computationally intensive model (2014) — 60 citations
- Future of nuclear fission theory (2020) — 162 citations
- Colloquium : Superheavy elements: Oganesson and beyond (2019) — 135 citations
- Energy Density Functional Methods for Atomic Nuclei (2019) — 153 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