Dr. Pascal Fernsel
Research Assistant WG Industrial Mathematics, Research Training Group π3Information: Email ends with @uni-bremen.de
Research Areas
- Matrix Factorizations for Machine Learning
- Clustering
- Inverse Problems
- Imaging mass spectrometry
Projects
- Nicht-negative Matrix-Faktorisierung mit A-priori-Wissen (since 01.12.2014)
Courses (Selection)
- Inverse Problems in Imaging (Wintersemester 2023/2024)
- Deep Learning for Inverse Problems (Sommersemester 2023)
- Nonlinear Inverse Problems (Sommersemester 2023)
Theses (Selection)
- Hauptkomponentenanalyse zur Untersuchung seismologischer Daten der Neumayer-Station III (Ribana Werner)
Publications (Selection)
- S. Arridge, P. Fernsel, A. Hauptmann.
Joint Reconstruction and Low-Rank Decomposition for Dynamic Inverse Problems.
Inverse Problems and Imaging, 16(3):483-523, 2022.DOI: 10.3934/ipi.2021059
- P. Fernsel.
Nonnegative Matrix Factorization: Theory, Algorithms and Applications.
Dissertationsschrift, Universität Bremen, 2022.DOI: 10.26092/elib/1493
online at: https://doi.org/10.26092/elib/1493 - P. Fernsel.
Spatially Coherent Clustering Based on Orthogonal Nonnegative Matrix Factorization.
MDPI Journal of Imaging, 7(10), 2021.DOI: 10.3390/jimaging7100194
online at: https://www.mdpi.com/2313-433X/7/10/194 - P. Fernsel, P. Maaß.
Regularized Orthogonal Nonnegative Matrix Factorization and K-means Clustering.
Zur Veröffentlichung eingereicht.online at: https://arxiv.org/abs/2112.07641
- J. Leuschner, M. Schmidt, P. Fernsel, D. Lachmund, T. Boskamp, P. Maaß.
Supervised Non-negative Matrix Factorization Methods for MALDI Imaging Applications.
Bioinformatics, bty909 , 2018.