Zahra Monfared

According to our database1, Zahra Monfared authored at least 15 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
On the algebra of Koopman eigenfunctions and on some of their infinities.
CoRR, April, 2026

Multimodal Deep Learning for Dynamic and Static Neuroimaging: Integrating MRI and fMRI for Alzheimer Disease Analysis.
CoRR, March, 2026

Electrocardiogram Classification with Transformers Using Koopman and Wavelet Features.
CoRR, March, 2026

Contrastive and Multi-Task Learning on Noisy Brain Signals with Nonlinear Dynamical Signatures.
CoRR, January, 2026

2025
Detecting Invariant Manifolds in ReLU-Based RNNs.
CoRR, October, 2025

2024
Gradient-free training of recurrent neural networks.
CoRR, 2024

Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Out-of-Domain Generalization in Dynamical Systems Reconstruction.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Bifurcations and loss jumps in RNN training.
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.
Proceedings of the International Conference on Machine Learning, 2023

2022
On the difficulty of learning chaotic dynamics with RNNs.
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.
Proceedings of the International Conference on Machine Learning, 2022

2021
How to train RNNs on chaotic data?
CoRR, 2021

Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Transformation of ReLU-based recurrent neural networks from discrete-time to continuous-time.
Proceedings of the 37th International Conference on Machine Learning, 2020


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