Physics-Informed Spectral Modeling for Hyperspectral Imaging

Zuzanna Gawrysiak, Krzysztof Krawiec
8/29/2025
cs.LGcs.AI

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Abstract

We present PhISM, a physics-informed deep learning architecture that learns without supervision to explicitly disentangle hyperspectral observations and model them with continuous basis functions. \mname outperforms prior methods on several classification and regression benchmarks, requires limited labeled data, and provides additional insights thanks to interpretable latent representation.

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Cite this paper

@article{gawrysiak2025physicsinformed,
  title  = {Physics-Informed Spectral Modeling for Hyperspectral Imaging},
  author = {Zuzanna Gawrysiak and Krzysztof Krawiec},
  year   = {2025},
  eprint = {2508.21618},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2508.21618v1}
}

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