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Found 2 papers, 1 papers with code
Deep Residual Error and Bag-of-Tricks Learning for Gravitational Wave Surrogate Modeling
In several cases, small improvements can be observed, but the most significant improvement still comes from the addition of a second network that models the residual error.
Autoencoder-driven Spiral Representation Learning for Gravitational Wave Surrogate Modelling
Based on this finding, we design a spiral module with learnable parameters, that is used as the first layer in a neural network, which learns to map the input space to the coefficients.
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