Researcher Portfolio
Engelken, Rainer
Department of Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, Research Group Theoretical Neurophysics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society
Researcher Profile
Position: Department of Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society
Position: Research Group Theoretical Neurophysics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society
Researcher ID: https://pure.mpg.de/cone/persons/resource/persons215422
Publications
: Engelken, R. (2023). SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks. arXiv. doi:10.48550/arXiv.2312.17216. [PubMan] : Engelken, R., Wolf, F., & Abbott, L. F. (2023). Lyapunov spectra of chaotic recurrent neural networks. Physical Review Research, 5(4): 043044. doi:10.1103/PhysRevResearch.5.043044. [PubMan] : Palmigiano, A., Engelken, R., & Wolf, F. (2023). Boosting of neural circuit chaos at the onset of collective oscillations. eLife, Reviewed Preprint. doi:10.7554/eLife.90378.1. [PubMan] : Engelken, R. (2017). Chaotic neural circuit dynamics. PhD Thesis, Georg-August-Universität, Göttingen. [PubMan]