Haiyang Fu

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 Haiyang Fu 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

Papers from Haiyang Fu's perspective

Ordered by how strongly the researchers Haiyang Fu 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. Learning partial differential equations via data discovery and sparse optimization
8. Image restoration: Total variation, wavelet frames, and beyond
9. PDE-Net: Learning PDEs from Data
10. PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network (Journal of Computational Physics)

Their papers

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