Manuel Brenner

According to our database, Manuel Brenner authored at least 11 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Uncovering the Computational Roles of Nonlinearity in Sequence Modeling Using Almost-Linear RNNs.

Manuel Brenner, Georgia Koppe

Trans. Mach. Learn. Res., 2026

2025

Uncovering the Functional Roles of Nonlinearity in Memory.

Manuel Brenner, Georgia Koppe

CoRR, June, 2025

Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data.

Manuel Brenner, Elias Weber, Georgia Koppe, Daniel Durstewitz

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Learning Interpretable Dynamical Systems Models from Multimodal Empirical Time Series.

Manuel Brenner

PhD thesis, 2024

Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction.

Manuel Brenner, Christoph Jürgen Hemmer, Zahra Monfared, Daniel Durstewitz

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction.

Christoph Jürgen Hemmer, Manuel Brenner, Florian Hess, Daniel Durstewitz

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Out-of-Domain Generalization in Dynamical Systems Reconstruction.

Niclas Alexander Göring, Florian Hess, Manuel Brenner, Zahra Monfared, Daniel Durstewitz

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics.

Manuel Brenner, Florian Hess, Georgia Koppe, Daniel Durstewitz

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Generalized Teacher Forcing for Learning Chaotic Dynamics.

Florian Hess, Zahra Monfared, Manuel Brenner, Daniel Durstewitz

Proceedings of the International Conference on Machine Learning, 2023

2022

Multimodal Teacher Forcing for Reconstructing Nonlinear Dynamical Systems.

Manuel Brenner, Georgia Koppe, Daniel Durstewitz

CoRR, 2022

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

Proceedings of the International Conference on Machine Learning, 2022