Wolfgang Betz

Statistics and Probability · 2014–2020

A researcher in the Science corpus: 3 papers; trusts 22 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 33 citations into it; #8,352 of 12,932 by trust here, #6,552 by citations
• Civil and Structural Engineering — 12 citations into it
• Artificial Intelligence — 11 citations into it
• Environmental Engineering — 10 citations into it
• Probabilistic & Bayesian Methods — 7 citations into it
• Mechanics of Materials — 6 citations into it; #4,542 of 6,291 by trust here, #4,968 by citations
• Safety, Risk, Reliability and Quality — 5 citations into it; #918 of 1,220 by trust here, #865 by citations

Whom Wolfgang Betz trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kok-Kwang Phoon
2. George Stefanou
3. Christoph Schwab
4. S. Quek
5. Alexander Düster
6. Jamshid Parvizian
7. Siu-Kui Au
8. Shuping Huang
9. Hong-wei Huang
10. Radu Alexandru Todor

Who trusts Wolfgang Betz overall

1. Iason Papaioannou
2. Daniel Straub
3. Sharmila Karumuri
4. Stefano Peluchetti
5. Diego A. Alvarez
6. Rohit Tripathy
7. Kai Cheng

Papers from Wolfgang Betz's perspective

Ordered by how strongly the researchers Wolfgang Betz trusts endorse each paper. Same corpus, a different order for every researcher.

1. Implementation of Karhunen-Loeve expansion for simulation using a wavelet-Galerkin scheme
2. Convergence study of the truncated Karhunen–Loeve expansion for simulation of stochastic processes
3. Comparison between KarhunenLoeve and wavelet expansions for simulation of Gaussian processes
4. The finite cell method for three-dimensional problems of solid mechanics
5. Regression and Classification Using Gaussian Process Priors
6. Finite elements for elliptic problems with stochastic coefficients
7. Karhunen-Loève approximation of random fields by generalized fast multipole methods (Journal of Computational Physics)
8. Modified Metropolis–Hastings algorithm with reduced chain correlation for efficient subset simulation
9. Small and large deformation analysis with the p- and B-spline versions of the Finite Cell Method
10. Simulation of strongly non-Gaussian processes using Karhunen–Loeve expansion

Their papers

• MCMC algorithms for Subset Simulation (2015) — 389 citations
• Numerical methods for the discretization of random fields by means of the Karhunen–Loève expansion (2014) — 312 citations
• Bayesian inference of random fields represented with the Karhunen–Loève expansion (2020) — 53 citations