Zahra Monfared

According to our database, Zahra Monfared authored at least 10 papers between 2020 and 2024.

Collaborative distances:

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

2024

Gradient-free training of recurrent neural networks.

Erik Lien Bolager, Ana Cukarska, Iryna Burak, Zahra Monfared, Felix Dietrich

CoRR, 2024

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

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

CoRR, 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

2023

Bifurcations and loss jumps in RNN training.

Lukas Eisenmann, Zahra Monfared, Niclas Alexander Göring, Daniel Durstewitz

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

On the difficulty of learning chaotic dynamics with RNNs.

Jonas M. Mikhaeil, Zahra Monfared, Daniel Durstewitz

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 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

2021

How to train RNNs on chaotic data?

Zahra Monfared, Jonas M. Mikhaeil, 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

2020

Transformation of ReLU-based recurrent neural networks from discrete-time to continuous-time.

Zahra Monfared, Daniel Durstewitz

Proceedings of the 37th International Conference on Machine Learning, 2020