Standout Papers
- Physics-informed machine learning (2021)
- Understanding and Mitigating Gradient Flow Pathologies in Physics-Informed Neural Networks (2021)
- Physics-Informed Neural Networks for Heat Transfer Problems (2021)
- When and why PINNs fail to train: A neural tangent kernel perspective (2021)
- Learning the solution operator of parametric partial differential equations with physics-informed DeepONets (2021)
- On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks (2021)
- Respecting causality for training physics-informed neural networks (2024)
Immediate Impact
7 from Science/Nature 63 standout
Citing Papers
Variational Physics-informed Neural Operator (VINO) for solving partial differential equations
2025 Standout
DeepOKAN: Deep operator network based on Kolmogorov Arnold networks for mechanics problems
2025 Standout
Works of Sifan Wang being referenced
Learning the solution operator of parametric partial differential equations with physics-informed DeepONets
2021 Standout
When and why PINNs fail to train: A neural tangent kernel perspective
2021 Standout
Author Peers
| Author | Last Decade | Papers | Cites | ||||
|---|---|---|---|---|---|---|---|
| Sifan Wang | 3372 | 1493 | 108 | 1104 | 15 | 6.1k | |
| Liu Yang | 2072 | 945 | 65 | 811 | 17 | 4.4k | |
| Lu Lu | 2731 | 1153 | 111 | 1049 | 75 | 6.4k | |
| Joshua L. Proctor | 3485 | 1480 | 134 | 971 | 44 | 6.1k | |
| C Moler | 852 | 1504 | 1763 | 726 | 48 | 9.5k | |
| Maziar Raissi | 6904 | 3031 | 260 | 2154 | 29 | 12.5k | |
| Roland Bulirsch | 784 | 1291 | 1675 | 328 | 43 | 7.8k | |
| C. W. Gear | 1243 | 2231 | 2675 | 264 | 90 | 8.9k | |
| Jianxun Wang | 1446 | 1082 | 25 | 356 | 156 | 4.5k | |
| D. C. Sorensen | 991 | 1557 | 1590 | 405 | 56 | 6.0k | |
| Juliette Florentin | 774 | 513 | 264 | 319 | 16 | 6.1k |
All Works
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