Encoding Raman spectra as global NMF coordinates plus local region-wise SVD modes reduces TabPFN regression error by 19.6% and classification error by 9.0% across 150 tasks.
Deep spectral component filtering as a foundation model for spectral analysis demonstrated in metabolic profiling.Nature Machine Intelligence, 7(5):743–757, 2025
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RamanPFN: learning from Raman spectral structure with a tabular foundation model
Encoding Raman spectra as global NMF coordinates plus local region-wise SVD modes reduces TabPFN regression error by 19.6% and classification error by 9.0% across 150 tasks.