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Parameter inversion on WInv (MAE)

Parameter inversion on WInv (MAE)

0.114MAEP-PINN

Updated 8mo ago

Evaluation results

Method	Links
P-PINN2026.02		0.114
PINN2026.02		0.199
D-PINN2026.02		0.314
B-PINN2026.02		0.425

State-of-the-art paper

P-PINN

Unlearning Noise in PINNs: A Selective Pruning Framework for PDE Inverse Problems

Dataset

WInv

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Related benchmarks

Data Assimilation on Poisson Data Assimilation on Heat Data assimilation on Wave Data Assimilation on Stokes Parameter inversion on PInv

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