| Odeint-solving ordinary differential equations in c++ K Ahnert, M Mulansky arXiv preprint arXiv:1110.3397, 2011 | 304 | 2011 |
| SPIKY: a graphical user interface for monitoring spike train synchrony T Kreuz, M Mulansky, N Bozanic Journal of neurophysiology 113 (9), 3432-3445, 2015 | 79 | 2015 |
| Dynamical thermalization of disordered nonlinear lattices M Mulansky, K Ahnert, A Pikovsky, DL Shepelyansky Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 80 (5 …, 2009 | 73 | 2009 |
| PySpike—A Python library for analyzing spike train synchrony M Mulansky, T Kreuz SoftwareX 5, 183-189, 2016 | 60 | 2016 |
| Strong and weak chaos in weakly nonintegrable many-body Hamiltonian systems M Mulansky, K Ahnert, A Pikovsky, DL Shepelyansky Journal of Statistical Physics 145, 1256-1274, 2011 | 58 | 2011 |
| Spreading in disordered lattices with different nonlinearities M Mulansky, A Pikovsky Europhysics Letters 90 (1), 10015, 2010 | 56 | 2010 |
| Energy spreading in strongly nonlinear disordered lattices M Mulansky, A Pikovsky New Journal of Physics 15 (5), 053015, 2013 | 52 | 2013 |
| Scaling of energy spreading in strongly nonlinear disordered lattices M Mulansky, K Ahnert, A Pikovsky Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 83 (2 …, 2011 | 45 | 2011 |
| Measures of spike train synchrony for data with multiple time scales E Satuvuori, M Mulansky, N Bozanic, I Malvestio, F Zeldenrust, K Lenk, ... Journal of neuroscience methods 287, 25-38, 2017 | 38 | 2017 |
| Solving ordinary differential equations on GPUs K Ahnert, D Demidov, M Mulansky Numerical Computations with GPUs, 125-157, 2014 | 35 | 2014 |
| A guide to time-resolved and parameter-free measures of spike train synchrony M Mulansky, N Bozanic, A Sburlea, T Kreuz 2015 International Conference on Event-based Control, Communication, and …, 2015 | 31 | 2015 |
| Leaders and followers: Quantifying consistency in spatio-temporal propagation patterns T Kreuz, E Satuvuori, M Pofahl, M Mulansky New Journal of Physics 19 (4), 043028, 2017 | 28 | 2017 |
| Scaling properties of energy spreading in nonlinear Hamiltonian two-dimensional lattices M Mulansky, A Pikovsky Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 86 (5 …, 2012 | 19 | 2012 |
| Localization properties of nonlinear disordered lattices M Mulansky Universität Potsdam, 2009 | 16 | 2009 |
| Using spike train distances to identify the most discriminative neuronal subpopulation E Satuvuori, M Mulansky, A Daffertshofer, T Kreuz Journal of neuroscience methods 308, 354-365, 2018 | 12 | 2018 |
| SPIKE-Synchronization: a parameter-free and time-resolved coincidence detector with an intuitive multivariate extension T Kreuz, N Bozanic, M Mulansky BMC Neuroscience 16 (Suppl 1), P170, 2015 | 11 | 2015 |
| Metaprogramming applied to numerical problems M Mulansky, K Ahnert arXiv preprint arXiv:1110.3233, 2011 | 8 | 2011 |
| Odeint library M Mulansky, K Ahnert Scholarpedia 9 (12), 32342, 2014 | 7 | 2014 |
| Re-localization due to finite response times in a nonlinear Anderson chain M Mulansky, AS Pikovsky The European Physical Journal B 85, 1-3, 2012 | 7 | 2012 |
| Scaling of chaos in strongly nonlinear lattices M Mulansky Chaos: An Interdisciplinary Journal of Nonlinear Science 24 (2), 2014 | 6 | 2014 |
Thomas KreuzSenior Researcher, Institute of Complex Systems (CNR), Florence, ItalyEmail verificata su cnr.it
