Christian Kuehn, Ph.D.
Affiliations: | 2010 | Cornell University, Ithaca, NY, United States |
Area:
Dynamical systemsGoogle:
"Christian Kuehn"Mean distance: 15.48
Parents
Sign in to add mentor| John Guckenheimer | grad student | 2010 | Cornell | |
| (Multiple time scale dynamics with two fast variables and one slow variable.) | ||||
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Publications
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| Mulas R, Kuehn C, Jost J. (2020) Coupled dynamics on hypergraphs: Master stability of steady states and synchronization. Physical Review. E. 101: 062313 |
| Horstmeyer L, Kuehn C. (2020) Adaptive voter model on simplicial complexes. Physical Review. E. 101: 022305 |
| Breden M, Kuehn C. (2020) Computing Invariant Sets of Random Differential Equations Using Polynomial Chaos Siam Journal On Applied Dynamical Systems. 19: 577-618 |
| Kuehn C. (2020) Network Dynamics on Graphops New Journal of Physics. 22: 53030 |
| Kuehn C, Neamţu A. (2020) Pathwise mild solutions for quasilinear stochastic partial differential equations Journal of Differential Equations. 269: 2185-2227 |
| Eichinger K, Kuehn C, Neamţu A. (2020) Sample Paths Estimates for Stochastic Fast-Slow Systems Driven by Fractional Brownian Motion Journal of Statistical Physics. 179: 1222-1266 |
| Kuehn C, Kürschner P. (2020) Combined error estimates for local fluctuations of SPDEs Advances in Computational Mathematics. 46 |
| Kojakhmetov HJ, Kuehn C. (2020) On Fast–Slow Consensus Networks with a Dynamic Weight Journal of Nonlinear Science. 1-50 |
| Kuehn C, Neamţu A, Pein A. (2020) Random attractors for stochastic partly dissipative systems Nodea-Nonlinear Differential Equations and Applications. 27 |
| Kuehn C, Tölle JM. (2019) A gradient flow formulation for the stochastic Amari neural field model. Journal of Mathematical Biology |