Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems. - Manuel Brenner; Florian Hess; Jonas M. Mikhaeil; Leonard F. Bereska; Zahra Monfared; Po-Chen Kuo; Daniel Durstewitz (ICML, 2022)

Multimodal Teacher Forcing for Reconstructing Nonlinear Dynamical Systems. - Manuel Brenner; Georgia Koppe; Daniel Durstewitz (CoRR, 2022)

Generalized Teacher Forcing for Learning Chaotic Dynamics. - Florian Hess; Zahra Monfared; Manuel Brenner; Daniel Durstewitz (ICML, 2023)

Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics. - Manuel Brenner; Florian Hess; Georgia Koppe; Daniel Durstewitz (ICML, 2024)

Out-of-Domain Generalization in Dynamical Systems Reconstruction. - Niclas Alexander Göring; Florian Hess; Manuel Brenner; Zahra Monfared; Daniel Durstewitz (ICML, 2024)

Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction. - Christoph Jürgen Hemmer; Manuel Brenner; Florian Hess; Daniel Durstewitz (ICML, 2024)

Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction. - Manuel Brenner; Christoph Jürgen Hemmer; Zahra Monfared; Daniel Durstewitz (NeurIPS, 2024)

Learning Interpretable Dynamical Systems Models from Multimodal Empirical Time Series. - Manuel Brenner (2024)

Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data. - Manuel Brenner; Elias Weber; Georgia Koppe; Daniel Durstewitz (ICLR, 2025)

Uncovering the Functional Roles of Nonlinearity in Memory. - Manuel Brenner; Georgia Koppe (CoRR, 2025)