Liang Yan

Statistics and Probability · 2010–2018

A researcher in the Science corpus: 3 papers; trusts 39 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 26 citations into it; #6,398 of 12,932 by trust here, #10,275 by citations
• Computational Mechanics — 14 citations into it
• Applied Mathematics — 11 citations into it
• Artificial Intelligence — 11 citations into it; #17,603 of 35,345 by trust here, #31,361 by citations
• Statistical and Nonlinear Physics — 11 citations into it
• Computational Theory and Mathematics — 9 citations into it
• Mathematical Physics — 9 citations into it
• Environmental Engineering — 6 citations into it

Whom Liang Yan trusts overall

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

1. Dongbin Xiu
2. Andrew M. Stuart
3. Youssef M. Marzouk
4. Albert Tarantola
5. Daniel Lesnic
6. Yumin Lin
7. Habib N. Najm
8. Jingbo Wang
9. Lionel Mathelin
10. Nicholas Zabaras

Who trusts Liang Yan overall

1. Guofei Pang
2. G. Em Karniadakis
3. Lu Lu
4. Paris Perdikaris
5. Wei Cai

Papers from Liang Yan's perspective

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

1. The Wiener-Askey Polynomial Chaos for Stochastic Differential Equations (SIAM Journal on Scientific Computing)
2. High-Order Collocation Methods for Differential Equations with Random Inputs (SIAM Journal on Scientific Computing)
3. Inverse problem theory - and methods for model parameter estimation
4. Statistical and Computational Inverse Problems (Technometrics)
5. Stochastic spectral methods for efficient Bayesian solution of inverse problems (Journal of Computational Physics)
6. Inverse problems: A Bayesian perspective (Acta Numerica)
7. Efficient Collocational Approach for Parametric Uncertainty Analysis (Communications in Computational Physics)
8. Inverse problems as statistics
9. Sparse grid collocation schemes for stochastic natural convection problems (Journal of Computational Physics)
10. A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (SIAM Review)

Their papers

• Stochastic Collocation Algorithms Using l1-Minimization for Bayesian Solution of Inverse Problems (2015) — 32 citations
• Adaptive multi-fidelity polynomial chaos approach to Bayesian inference in inverse problems (2018) — 120 citations
• A computational method for identifying a spacewise‐dependent heat source (2010) — 52 citations