Zhao Chen

Statistical and Nonlinear Physics · with Liu · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 19 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Statistical and Nonlinear Physics — 43 citations into it; #6,707 of 10,127 by trust here, #9,682 by citations
• Artificial Intelligence — 23 citations into it
• Computational Mechanics — 19 citations into it; #6,968 of 10,001 by trust here, #9,582 by citations
• AI for Physical Sciences — 15 citations into it
• Control and Systems Engineering — 11 citations into it
• Statistics and Probability — 11 citations into it; #9,181 of 12,932 by trust here, #12,077 by citations
• Molecular Biology — 10 citations into it
• Optimization & Training — 10 citations into it

Whom Zhao Chen trusts overall

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

1. Steven L. Brunton
2. Hayden Schaeffer
3. Ilya M. Sobol
4. J. Nathan Kutz
5. Joshua L. Proctor
6. Samuel H. Rudy
7. Richard H. Byrd
8. Kathleen P. Champion
9. Maizar Raissi
10. Bethany Lusch

Who trusts Zhao Chen overall

1. Benjamin Moseley
2. Fujin Wang
3. Andrew Markham
4. Ruiyang Zhang
5. Zhi Zhai
6. Yang Liu
7. T. Nissen‐Meyer

Papers from Zhao Chen's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Long Short-Term Memory
6. Regression Shrinkage and Selection via the Lasso
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Deep learning of physical laws from scarce data (2020) — 19 citations
• Physics-informed learning of governing equations from scarce data (2020) — 661 citations
• Deep long short-term memory networks for nonlinear structural seismic response prediction (2019) — 501 citations