DSAI Dynamical Systems and Artificial Intelligence

Publications

2026

  1. A. Kujur, Z. Monfared, S. Safavi, "Koopman-based transient dynamics reconstruction", Accepted at COSYNE, 2026.
  2. S. Ghosh, F. Dietrich, Z. Monfared, "Contrastive and Multi-Task Learning on Noisy EEG Brain Signals with Nonlinear Dynamical Signatures", arXiv:2601.08549, 2026.
  3. S. Ghosh, F. Dietrich, Z. Monfared, "Contrastive and Multi-Task Learning on Noisy EEG Brain Signals with Nonlinear Dynamical Signatures", arXiv:2601.08549, 2026.
  4. L. Eisenmann, A. Braendle, Z. Monfared, D. Durstewitz, "Detecting Invariant Manifolds in ReLU-Based RNNs, International Conference on Learning Representations (ICLR)", 2026.

2025

  1. A. Liatsetskaya, Z. Monfared, C. Datar, F. Dietrich, "Recurrent Neural Network-based error estimator in spectral methods for solving PDEs", DTE & AICOMAS 2025, Paris, France, 2025.
  2. A. Kujur, Z. Monfared, F. Dietrich, "Multimodal Deep Learning for Dynamic and Static Neuroimaging: Integrating MRI and fMRI for Alzheimer’s Disease Analysis", DTE & AICOMAS 2025, Paris, France, 2025.
  3. H. Schwab, Z. Monfared, F. Dietrich, "Koopman Analysis of the Heat Equation", Dynamics Days Europe 2025 conference, 2025.
  4. S. Ghosh, Z. Monfared, F. Dietrich, "Self-Supervised Contrastive Learning with Denoising Autoencoders for Robust Event- Related Potential Classification in Noisy EEG Signals for Brain-Computer Interface Motor Tasks", Dynamics Days Europe 2025 conference, 2025.
  5. A. Alshembari , A. Kujur, Z. Monfared, "Deep Spatio-temporal Learning in fMRI Sequence Prediction for Alzheimer’s Disease", 2nd Sorbonne-Heidelberg Workshop on AI in medicine, 2025.
  6. M. Baharifar, A. Kujur, Z. Monfared, "IntAI for Classifying Human- and LLM-Generated Medical Misinformation with Multi-Modal Features", 2nd Sorbonne-Heidelberg Workshop on AI in medicine, 2025.
  7. S. Ghosh, H. A. Liatsetskaya, H. Schwab, F. Dietrich, Z. Monfared, "Multiscale Denoising Autoencoder with Fourier and Wavelet Representations for Robust Air Quality Time Series Classification: A Comparative Study with Transformers", MSML 2025, 2025.
  8. A. Kujur, Z. Monfared and S. Safavi, "Transient Neural Dynamics Reconstruction", NeurIPS Workshop on Learning from Time Series for Health, 2025.
  9. A. Alshembari, A. Kujur and Z. Monfared, "Autoregressive ConvLSTM Framework for fMRI Time Series Forecasting in Alzheimer’s Disease", NeurIPS Workshop on Learning from Time Series for Health, 2025.

2024

  1. A. Datar, C. Datar, Z. Monfared, F. Dietrich, "Role of Parametrization in Learning Dynamics of Recurrent Neural Networks",NeurIPS OPT2024, 2024.
  2. E. L. Bolager, A. Cukarska, I. Burak, Z. Monfared, F. Dietrich, "Gradient-free training of recurrent neural networks," https://arxiv.org/abs/2410.23467, 2024.
  3. A. Datar, C. Datar, Z. Monfared, F. Dietrich, "Role of Parameterization in Learning Dynamics of Recurrent Neural Networks," NeurIPS OPT2024, 2024.
  4. M. Brenner, C. Hemmer, Z. Monfared, D. Durstewitz, "Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction," Advances in Neural Information Processing Systems (NeurIPS 2024), 2024.
  5. N. Göring, F. Hess, M. Brenner, Z. Monfared, D. Durstewitz, "Out-of-Domain Generalization in Dynamical Systems Reconstruction," Proceedings of Machine Learning Research (ICML 2024), 2024.
  6. L. Eisenmann, Z. Monfared, N. Göring, D. Durstewitz, "Bifurcations and loss jumps in RNN training," Advances in Neural Information Processing Systems (NeurIPS 2023), 2024.
  7. Z. Monfared, S. Malhotra, S. Hajime, I. Kevrekidis, F. Dietrich, "On the algebra of Koopman eigenfunctions," Preprint, 2024.

2023

  1. F. Hess, Z. Monfared, M. Brenner, D. Durstewitz, "Generalized Teacher Forcing for Learning Chaotic Dynamics," Proceedings of Machine Learning Research (ICML 2023), 2023.

2022

  1. *J. Mikhaeil, *Z. Monfared, D. Durstewitz, "On the difficulty of learning chaotic dynamics with RNNs," Neural Information Processing Systems (NeurIPS 2022), 2022.
  2. M. Brenner, F. Hess, J. Mikhaeil, L. Bereska, Z. Monfared, P-C. Kuo, D. Durstewitz, "Tractable dendritic RNNs for reconstructing nonlinear dynamical systems," Proceedings of Machine Learning Research (ICML 2022), Vol. 162, pp. 2292-2320, 2022.
  3. Z. Monfared, M. Patra, D. Durstewitz, "Robust chaos and multi-stability in piecewise linear recurrent neural networks," Research Square, 2022.
  4. P. H. Maleki, Z. Monfared, Y. Golzadeh, Y. Qaseminezhad Raeini, "A brief overview of recurrent neural networks from dynamical systems perspective," 53rd Annual Iranian Mathematics Conference, 2022.

2021

  1. D. Schmidt, G. Koppe, Z. Monfared, M. Beutelspacher, D. Durstewitz, "Identifying nonlinear dynamical systems with multiple time scales and long-range dependencies," International Conference on Learning Representations (ICLR 2021), 2021.
  2. Z. Monfared, Z. Dadi, A. Darijani, Y. Qaseminezhad Raeini, "Dynamics of a harmonic oscillator perturbed by a non-smooth velocity-dependent damping force," Journal of Mahani Mathematical Research Center, Vol. 10, pp. 145-162, 2021.

2020

  1. Z. Monfared, D. Durstewitz, "Transformation of ReLU-based recurrent neural networks from discrete-time to continuous-time," Proceedings of Machine Learning (ICML 2020), Vol. 119, pp. 6999-7009, 2020.
  2. Z. Monfared, D. Durstewitz, "Existence of n-cycles and border-collision bifurcations in piecewise-linear continuous maps with applications to recurrent neural networks," Nonlinear Dynamics, Vol. 101, 2020.
  3. Z. Monfared, F. Omidi, Y. Qaseminezhad Raeini, "Investigating the effect of pyroptosis on the slow CD4+ T cell depletion in HIV-1 infection, by dynamical analysis of its discontinuous mathematical model," International Journal of Biomathematics, Vol. 13, No. 06, 2050041, 2020.
  4. Z. Monfared, Z. Dadi, Z. Afsharnezhad, "Lyapunov exponents for discontinuous dynamical systems of Filippov type," Computational Methods for Differential Equations, Vol. 8, No. 3, 2020.