Jesper Løve Hinrich
Guest researcher, Guest Researcher
ORCID: 0000-0003-0258-7151
1 - 5 out of 5Page size: 10
- 2024
- Accepted/In press
Probabilistic Block Term Decomposition for the Modelling of Higher-order Arrays
Hinrich, Jesper Løve & Morup, M., 2024, (Accepted/In press) In: Computing in Science and Engineering.Research output: Contribution to journal › Journal article › Research › peer-review
- 2023
- Published
Multiway Decomposition Followed by Reconvolution of Fluorescence Time Decay Data
Risum, Anne Bech, Hinrich, Jesper Løve & Rinnan, Åsmund, 2023, In: Analytical Chemistry. 95, 51, p. 18697-18708 12 p.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
PARAFAC2×N: Coupled decomposition of multi-modal data with drift in N modes
Sorochan Armstrong, M. D., Hinrich, Jesper Løve, de la Mata, A. P. & Harynuk, J. J., 2023, In: Analytica Chimica Acta. 1249, 14 p., 340909.Research output: Contribution to journal › Journal article › Research › peer-review
- 2022
- Published
Using machine learning to identify quality-of-care predictors for emergency caesarean sections: a retrospective cohort study
Andersen, Betina Ristorp, Ammitzboll, I., Hinrich, Jesper Løve, Lehmann, S., Ringsted, C. V., Løkkegaard, Ellen Christine Leth & xgz472, xgz472, 2022, In: BMJ Open. 12, 3, 8 p., 049046.Research output: Contribution to journal › Journal article › Research › peer-review
- 2019
Probabilistic tensor train decomposition
Hinrich, Jesper Løve & Mørup, M., Sep 2019, In: European Signal Processing Conference.Research output: Contribution to journal › Conference article › Research › peer-review
ID: 242098644
Most downloads
-
27
downloads
Using machine learning to identify quality-of-care predictors for emergency caesarean sections: a retrospective cohort study
Research output: Contribution to journal › Journal article › Research › peer-review
Published