A conditioned autoencoder with position-dependent weights estimates acoustic transfer function magnitude distributions from sparse measurements, outperforming kernel ridge regression and neural field baselines in simulation.
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Learning Magnitude Distribution of Sound Fields via Conditioned Autoencoder
A conditioned autoencoder with position-dependent weights estimates acoustic transfer function magnitude distributions from sparse measurements, outperforming kernel ridge regression and neural field baselines in simulation.