XPINN
PulseAugur coverage of XPINN — every cluster mentioning XPINN across labs, papers, and developer communities, ranked by signal.
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New method improves training of physics-informed neural networks
Researchers have developed Norm-PCGrad, a novel method to improve the training of physics-informed neural networks (PINNs) and physics-informed Kolmogorov-Arnold Networks (PIKANs) when using domain decomposition. This t…
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New Bi-HYCO Framework Enhances PDE Parameter Identification with Fragmented Data
Researchers have introduced Bi-HYCO, a novel cooperative learning framework designed for identifying parameters in Partial Differential Equations (PDEs) when observations are fragmented. This method couples complementar…
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New TSDD-PINN framework improves traffic estimation from sparse sensors
Researchers have developed a new framework called Two-Stage Domain Decomposition Physics-Informed Neural Networks (TSDD-PINN) to improve traffic state estimation from sparse sensor data. This method addresses the tenden…