I'm an assistant professor in mathematics. My research concerns different kinds of machine learning, i.e. how we with the help of mathematics can help computers find patterns in large sets of data. I am especially interested in compressed sensing, which concerns methods utilizing structrial assumptions to aid reconstruction of signals from incomplete data, and equivariance in deep neural networks, which means that I investigate how symmetries in the data can be utilized, and how what effect these methods have. Jag obtained my PhD degree from the Technische Universität Berlin in 2018, and have since then worked in Toulouse and Gothenburg before arriving in Umeå.
2025
Transactions on Machine Learning Research
Nordenfors, Oskar; Ohlsson, Fredrik; Flinth, Axel
2025
Umeå: Umeå University 2025
Raman Sundström, Manya; Ewald, Christian Oliver; Lundow, Per-Håkan; et al.
2023
Image analysis: 23rd Scandinavian conference, SCIA 2023, Sirkka, Finland, April 18–21, 2023, proceedings, part II, Cham: Springer Nature 2023 : 59-76
Brynte, Lucas; Bökman, Georg; Flinth, Axel; et al.
2023
Transactions on Machine Learning Research
Bökman, Georg; Flinth, Axel; Kahl, Fredrik
2023
2023 6th International Conference on Advanced Communication Technologies and Networking (CommNet), IEEE 2023 : 1-8
Wunder, Gerhard; Flinth, Axel; Becker, Daniel; et al.
2023
IEEE Transactions on Information Theory, IEEE 2023, Vol. 69, (10) : 6719-6738
Wunder, Gerhard; Flinth, Axel; Gross, Benedikt
2022
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE Computer Society 2022 : 10966-10975