2024
Rauschenberg C., Schirmbeck F., Fechtelpeter J., Wierzba E., Hiller S., Kahr K., Koppe* G. & Reininghaus* U.
Effects of AI4U training, a machine learning-based, adaptive ecological momentary intervention for personalized mental health promotion in youth: findings from a micro-randomized trial
2024, October 13, https://doi.org/10.31234/osf.io/mvyar
Brenner* M., Weber* E., KoppeϮ G. & DurstewitzϮ D.
Learning interpretable hierarchical dynamical systems models from time series data
preprint arXiv: 2410.04814
Volkmann E., Braendle A., Durstewitz D. & Koppe G.
A scalable generative model for dynamical system reconstruction from neuroimaging data
Advances in Neural Information Processing Systems (accepted for publication),
Brenner M., Guennouni I., Durstewitz D., Schmidt S. N. L., Lis S., Kirsch P. & Koppe G.
Digital twins of human social interactions reveal behavioral strategies in exchange games
2024, September 20, https://doi.org/10.31234/osf.io/m6pnq
Brenner M., Hess F., Koppe G., Durstewitz D.
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics
Proceedings of the 41st International Conference on Machine Learning, PMLR 235:4482-4516, 2024
Fechtelpeter J., Rauschenberg C., Jamalabadi H., Boecking B., van Amelsvoort T., Reininghaus U., Durstewitz D., Koppe G.
A control theoretic approach to evaluate and inform ecological momentary interventions
International Journal of Methods in Psychiatric Research, 2024, e70001, https://doi.org/10.1002/mpr.70001
