Hybrid quantum-classical FBPINN for acoustic FWI achieves lower L1 velocity error than classical baselines in ~8x fewer iterations with ~33% fewer parameters on anomaly and checkerboard benchmarks.
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Systematic benchmark of PINN architectures on 1D stiff PNP system finds BRDR loss weighting competitive with NTK at lower wall-clock time.
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Accelerating physics-informed neural networks for full waveform inversion using a hybrid quantum-classical finite-basis architecture
Hybrid quantum-classical FBPINN for acoustic FWI achieves lower L1 velocity error than classical baselines in ~8x fewer iterations with ~33% fewer parameters on anomaly and checkerboard benchmarks.
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A Systematic Benchmark of Physics-Informed Neural Network Architectures for the Stiff Poisson-Nernst-Planck System: Adaptive LossWeighting and Multi-Scale Resolution
Systematic benchmark of PINN architectures on 1D stiff PNP system finds BRDR loss weighting competitive with NTK at lower wall-clock time.