Georgia Koppe

According to our database, Georgia Koppe authored at least 18 papers between 2014 and 2026.

Collaborative distances:

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

2026

The Dynamic-Probabilistic Consistency Gap in Chaotic Surrogate Modeling.

Andre Herz, Matthijs Pals, Daniel Durstewitz, Georgia Koppe

CoRR, May, 2026

Teacher Forcing as Generalized Bayes: Optimization Geometry Mismatch in Switching Surrogates for Chaotic Dynamics.

Andre Herz, Daniel Durstewitz, Georgia Koppe

CoRR, April, 2026

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

Manuel Brenner, Georgia Koppe

Trans. Mach. Learn. Res., 2026

Computational network models for forecasting and control of mental health trajectories in digital applications.

Janik Fechtelpeter, Christian Rauschenberg, Christian Goetzl, Selina Hiller, Eva Wierzba, Niklas Emonds, Silvia Krumm, Ulrich Reininghaus, Daniel Durstewitz, Georgia Koppe

npj Digit. Medicine, 2026

2025

What Neuroscience Can Teach AI About Learning in Continuously Changing Environments.

Daniel Durstewitz, Bruno Averbeck, Georgia Koppe

CoRR, July, 2025

Uncovering the Functional Roles of Nonlinearity in Memory.

Manuel Brenner, Georgia Koppe

CoRR, June, 2025

Deep Active Inference with Neural Stochastic Differential Equations.

Marc Pritsch, Georgia Koppe

Proceedings of the Active Inference - 6th International Workshop, 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

A scalable generative model for dynamical system reconstruction from neuroimaging data.

Eric Volkmann, Alena Brändle, Daniel Durstewitz, Georgia Koppe

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 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

2022

Multimodal Teacher Forcing for Reconstructing Nonlinear Dynamical Systems.

Manuel Brenner, Georgia Koppe, Daniel Durstewitz

CoRR, 2022

Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series.

Daniel Kramer, Philine Lou Bommer, Daniel Durstewitz, Carlo Tombolini, Georgia Koppe

Proceedings of the International Conference on Machine Learning, 2022

2021

Identifying nonlinear dynamical systems from multi-modal time series data.

Philine Lou Bommer, Daniel Kramer, Carlo Tombolini, Georgia Koppe, Daniel Durstewitz

CoRR, 2021

Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies.

Dominik Schmidt, Georgia Koppe, Zahra Monfared, Max Beutelspacher, Daniel Durstewitz

Proceedings of the 9th International Conference on Learning Representations, 2021

2019

Identifying nonlinear dynamical systems via generative recurrent neural networks with applications to fMRI.

Georgia Koppe, Hazem Toutounji, Peter Kirsch, Stefanie Lis, Daniel Durstewitz

PLoS Comput. Biol., 2019

Inferring Dynamical Systems with Long-Range Dependencies through Line Attractor Regularization.

Dominik Schmidt, Georgia Koppe, Max Beutelspacher, Daniel Durstewitz

CoRR, 2019

2015

Temporal unpredictability of a stimulus sequence and the processing of neutral and emotional stimuli.

Georgia Koppe, A. Heidel, Gebhard Sammer, M. Bohus, Bernd Gallhofer, Peter Kirsch, Stefanie Lis

NeuroImage, 2015

2014

Temporal unpredictability of a stimulus sequence affects brain activation differently depending on cognitive task demands.

Georgia Koppe, Harald Gruppe, Gebhard Sammer, Bernd Gallhofer, Peter Kirsch, Stefanie Lis

NeuroImage, 2014