Simon Wein, M.Sc. Physik

Research focus

• Matrix  factorization techniques
• Blind and semi-blind source separation
• Deep learning
• Brain connectivity

Publications

• Wein, S., Malloni, W., Tome, A.M., Frank, S., Henze, G-I., Wüst, S., Greenlee, M., Lang, E.. A graph neural network framework for causal inference in brain networks. Scientific Reports. 11. https://doi.org/10.1038/s41598-021-87411-8 (2021).

• Wein, S., Deco, G., Tome, A.M., Goldhacker, M., Malloni, W., Greenlee, M., Lang, E.. Brain Connectivity Studies on Structure- Function Relationships: A Short Survey with an Emphasis on Machine Learning. Computational Intelligence and Neuroscience. 2021. 1-31. https://doi.org/10.1155/2021/5573740 (2021).

• Wein, S., Malloni, W., Tome, A.M., Frank, S., Henze, G-I., Wüst, S., Greenlee, M., Lang, E.. A graph neural network framework for causal inference in brain networks. Scientific Reports. 11. https://doi.org/10.1038/s41598-021-87411-8 (2021).

• Wein, S., Tome, A.M., Goldhacker, M., Greenlee, M., Lang, E.. A Constrained ICA-EMD Model for Group Level fMRI Analysis. Frontiers in Neuroscience. 14. https://doi.org/10.3389/fnins.2020.00221 (2020).

Konferenzbeiträge

• Wein, S., Tome, A.M., Goldhacker, M., Greenlee, M., Lang, E. (2019). Hybridizing EMD with cICA for fMRI Analysis of Patient Groups. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 194-197. https://doi.org/10.1109/EMBC.2019.8856355 (2019).