Bayesian Spectral Deconvolution

Bayesian Spectral Deconvolution is a spectral deconvolution method that employs Bayesian inference to estimate the underlying spectral components by incorporating prior knowledge and probabilistic modeling of noise and parameter uncertainty.

11

Publications

638

Citations

35

Authors

22

Institutions

Publications per year

2017–2026

3

Authors

35

  1. JA
    Jessica A. Wales

    University of Arizona, United States

    1 publications · 128 citations

    1

    h-index

  2. ML
    Manuel Liebeke

    Universität Greifswald, Germany

    1 publications · 196 citations

    1

    h-index

  3. CL
    Claire L. Waterman

    Syngenta (United Kingdom), United Kingdom

    1 publications · 26 citations

    1

    h-index

  4. SM
    S. Marquardt

    Goethe University Frankfurt, Germany

    1 publications · 24 citations

    1

    h-index

  5. WM
    W.R. Montfort

    University of Arizona, United States

    1 publications · 128 citations

    1

    h-index

1–5 of 35

Venues

  1. Journal of the Physical Society of Japan

    2 publications · 75 citations

    2

    h-index

  2. Physical review. D/Physical review. D.

    PRD · 1 publications · 33 citations

    1

    h-index

  3. Neural Networks

    1 publications · 125 citations

    1

    h-index

  4. Journal of the American Society for Mass Spectrometry

    JASMS · 1 publications · 128 citations

    1

    h-index

  5. Physical review. B, Condensed matter

    PRB · 1 publications · 24 citations

    1

    h-index

1–5