Mixture of Experts for PINNs (MoE-PINNs) | by Rafael Bischof | Feb, 2023 | Towards Data Science
the structure of PINNs The total loss can be formulated as follow, | Download Scientific Diagram
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Algorithms | Free Full-Text | Physics-Informed Neural Networks (PINNs)-Based Traffic State Estimation: An Application to Traffic Network
Physics-informed neural networks (PINNs) for fluid mechanics: a review | SpringerLink
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Some libraries for solving O/PDEs using PINNs - 知乎
The deep learning frame based on the PINNs. | Download Scientific Diagram
Physics-informed neural networks (PINNs) for fluid mechanics: a review | SpringerLink
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Δ-PINNs: physics-informed neural networks on complex geometries | DeepAI
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nn-PINNs: Non-Newtonian physics-informed neural networks for complex fluid modeling - Soft Matter (RSC Publishing)
Frontiers | EP-PINNs: Cardiac Electrophysiology Characterisation Using Physics-Informed Neural Networks
Physics-Informed Neural Networks (PINNs) for Sound Field Predictions with Parameterized Sources and Impedance Boundaries - Nweon Paper
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Schematic of the PINNs for solving partial differential equations. | Download Scientific Diagram
