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Fast and accurate bandpass integration of complex SEDs with neural networks
The paper presents a novel ML-based approach for fast and accurate bandpass integration of spectral energy distributions (SEDs). The non-locality of the integral operator involved guarantees the smoothness of the target function to be approximated, making it an excellent use-case for neural networks
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