Bing Xiong

Statistical and Nonlinear Physics · 2019

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Statistical and Nonlinear Physics — 7 citations into it
• AI for Physical Sciences — 6 citations into it
• Artificial Intelligence — 5 citations into it
• Numerical Methods & Scientific Computing — 5 citations into it

Whom Bing Xiong trusts overall

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

1. Maizar Raissi
2. Hayden Schaeffer
3. Steven L. Brunton
4. Zichao Long
5. G. Em Karniadakis
6. Joshua L. Proctor
7. Samuel H. Rudy
8. J. Nathan Kutz
9. Paris Perdikaris
10. Yiping Lu

Papers from Bing Xiong's perspective

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

1. Automated reverse engineering of nonlinear dynamical systems
2. Discovering governing equations from data by sparse identification of nonlinear dynamical systems
3. Distilling Free-Form Natural Laws from Experimental Data
4. Data-driven discovery of partial differential equations
5. Hidden physics models: Machine learning of nonlinear partial differential equations
6. Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations
7. Regression Shrinkage and Selection via the Lasso
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Learning partial differential equations via data discovery and sparse optimization
10. PDE-Net: Learning PDEs from Data

Their papers

• Data-driven Discovery of Partial Differential Equations for Multiple-Physics Electromagnetic Problem (2019) — 17 citations