Standout Papers

A physics-informed variational DeepONet for predicting crack path in quasi-brittle material... 2021 2026 2022 2024881
  1. A physics-informed variational DeepONet for predicting crack path in quasi-brittle materials (2022)
    Somdatta Goswami, Minglang Yin et al. Computer Methods in Applied Mechanics and Engineering
  2. Physics-informed neural networks (PINNs) for fluid mechanics: a review (2021)
    Shengze Cai, Zhiping Mao et al. Acta Mechanica Sinica

Immediate Impact

2 from Science/Nature 72 standout
Sub-graph 1 of 19

Citing Papers

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1 intermediate paper

Works of Minglang Yin being referenced

Physics-informed neural networks (PINNs) for fluid mechanics: A review
2021

Author Peers

Author Last Decade Papers Cites
Minglang Yin 844 444 51 233 14 1.4k
Ehsan Kharazmi 906 435 2 187 14 1.2k
Zhicheng Wang 938 486 11 285 22 1.7k
Atılım Güneş Baydin 614 263 3 149 16 1.4k
Alexey Radul 616 263 2 121 11 1.2k
Vincenzo Schiano Di Cola 527 194 5 121 17 1.3k
Justin Sirignano 897 409 2 105 15 1.3k
Ehsan Haghighat 923 375 8 191 38 1.9k
Dunhui Xiao 1062 753 5 324 63 2.0k
Tan Bui–Thanh 729 658 23 152 52 1.6k
Konstantinos Spiliopoulos 945 419 2 107 42 1.4k

All Works

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2026