| Transient chaotic dimensionality expansion by recurrent networks C Keup, T Kühn, D Dahmen, M Helias Physical Review X 11 (2), 021064, 2021 | 24 | 2021 |
| Decomposing neural networks as mappings of correlation functions K Fischer, A René, C Keup, M Layer, D Dahmen, M Helias Physical review research 4 (4), 043143, 2022 | 13 | 2022 |
| Unfolding recurrence by Green’s functions for optimized reservoir computing S Nestler, C Keup, D Dahmen, M Gilson, H Rauhut, M Helias Advances in Neural Information Processing Systems 33, 17380-17390, 2020 | 6 | 2020 |
| Phase space analysis of chaotic neural networks J Stubenrauch, C Keup, AC Kurth, M Helias, A van Meegen arXiv preprint arXiv:2210.07877, 2022 | 3 | 2022 |
| Origami in N dimensions: How feed-forward networks manufacture linear separability C Keup, M Helias arXiv preprint arXiv:2203.11355, 2022 | 3 | 2022 |
| 26th annual computational neuroscience meeting (CNS* 2017): part 2 LL Rubchinsky, S Ahn, W Klijn, B Cumming, S Yates, V Karakasis, ... BMC neuroscience 18, 1-79, 2017 | 2 | 2017 |
| Optimal thresholds and algorithms for a model of multi-modal learning in high dimensions C Keup, L Zdeborová arXiv preprint arXiv:2407.03522, 2024 | 1 | 2024 |
| A neuron model independent path integral explored via binary assemblies C Keup, M Helias, T Kühn Computational and Systems Neuroscience, 2017 | 1 | 2017 |
| Neural networks learning structure in temporal signals S Nestler, D Dahmen, M Gilson, Y Boutaib, W Bartolomaeus, C Keup, ... Seminar Talk, Barak Lab, 2023 | | 2023 |
| Field theoretic approaches to computation in neuronal networks. C Keup, M Helias, M Krämer RWTH Aachen University, Germany, 2022 | | 2022 |
| Statistical decomposition of feed-forward neural networks: Transfer of information between correlation functions K Fischer, D Dahmen, C Keup, M Layer, M Helias, A Rene INM IBI Retreat 2022, 2022 | | 2022 |
| Transient chaotic SNR amplification C Keup, D Dahmen, M Helias, T Kühn COSYNE 2021, 2021 | | 2021 |
| Fluctuations, correlations, chaos: dynamics and computation in recurrent networks M Helias, D Dahmen, S Nestler, A van Meegen, C Keup MILA Seminar, 2021 | | 2021 |
| Code and data for: Keup et al.(2021) Transient Chaotic Dimensionality Expansion by Recurrent Networks. PRX 11, 021064 C Keup, D Dahmen, M Helias, T Kühn Computational and Systems Neuroscience, 2021 | | 2021 |
| Optimized Reservoir Computing with Stochastic Recurrent Networks S Nestler, D Dahmen, M Helias, C Keup CNS 2019 Barcelona, 2019 | | 2019 |
| Dynamics of Cell Assemblies in Binary Neuronal Networks C Keup, T Kühn, M Helias INSPIRE-New insights on complex neural dynamics, 2018 | | 2018 |
| X107 Dynamics of cell assemblies in binary neuronal networks C Keup, T Kühn, M Helias | | |
Moritz HeliasInst. for Neuroscience and medicine (INM-6), Jülich; Faculty of Physics, RWTH Aachen在 fz-juelich.de 的电子邮件经过验证
