| Objective comparison of methods to decode anomalous diffusion G Muñoz-Gil, G Volpe, MA Garcia-March, E Aghion, A Argun, CB Hong, ... Nature communications 12 (1), 6253, 2021 | 155 | 2021 |
| Classification of diffusion modes in single-particle tracking data: Feature-based versus deep-learning approach P Kowalek, H Loch-Olszewska, J Szwabiński Physical Review E 100 (3), 032410, 2019 | 113 | 2019 |
| Motion of influential players can support cooperation in prisoner’s dilemma M Droz, J Szwabiński, G Szabó The European Physical Journal B 71, 579-585, 2009 | 86 | 2009 |
| Classification of particle trajectories in living cells: Machine learning versus statistical testing hypothesis for fractional anomalous diffusion J Janczura, P Kowalek, H Loch-Olszewska, J Szwabiński, A Weron Physical Review E 102 (3), 032402, 2020 | 57 | 2020 |
| Is the person-situation debate important for agent-based modeling and vice-versa? K Sznajd-Weron, J Szwabiński, R Weron PloS one 9 (11), e112203, 2014 | 54 | 2014 |
| Conformity, anticonformity and polarization of opinions: insights from a mathematical model of opinion dynamics T Krueger, J Szwabiński, T Weron Entropy 19 (7), 371, 2017 | 53 | 2017 |
| Rewiring the network. What helps an innovation to diffuse? K Sznajd-Weron, J Szwabiński, R Weron, T Weron Journal of Statistical Mechanics: Theory and Experiment 2014 (3), P03007, 2014 | 37 | 2014 |
| The interplay between conformity and anticonformity and its polarizing effect on society P Siedlecki, J Szwabiński, T Weron arXiv preprint arXiv:1603.07556, 2016 | 30 | 2016 |
| Impact of feature choice on machine learning classification of fractional anomalous diffusion H Loch-Olszewska, J Szwabiński Entropy 22 (12), 1436, 2020 | 24 | 2020 |
| Complex population dynamics as a competition between multiple-time-scale phenomena I Bena, M Droz, J Szwabiński, A Pȩkalski Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 76 (1 …, 2007 | 18 | 2007 |
| Mapping the q-voter model: From a single chain to complex networks A Jȩdrzejewski, K Sznajd-Weron, J Szwabiński Physica A: Statistical Mechanics and its Applications 446, 110-119, 2016 | 17 | 2016 |
| Boosting the performance of anomalous diffusion classifiers with the proper choice of features P Kowalek, H Loch-Olszewska, Ł Łaszczuk, J Opała, J Szwabiński Journal of Physics A: Mathematical and Theoretical 55 (24), 244005, 2022 | 16 | 2022 |
| Extinction risk and structure of a food web model A Pękalski, J Szwabiński, I Bena, M Droz Physical Review E 77 (3), 031917, 2008 | 16 | 2008 |
| Effects of random habitat destruction in a predator–prey model J Szwabiński, A Pe Physica A: Statistical Mechanics and its Applications 360 (1), 59-70, 2006 | 15 | 2006 |
| Machine-learning solutions for the analysis of single-particle diffusion trajectories H Seckler, J Szwabinski, R Metzler The Journal of Physical Chemistry Letters 14 (35), 7910-7923, 2023 | 14 | 2023 |
| Best portfolio management strategies for synthetic and real assets J Gruszka, J Szwabiński Physica A: Statistical Mechanics and Its Applications 539, 122938, 2020 | 12 | 2020 |
| Detection of anomalous diffusion with deep residual networks M Gajowczyk, J Szwabiński Entropy 23 (6), 649, 2021 | 11 | 2021 |
| Food web model with detritus path J Szwabinski, A Pekalski, I Bena, M Droz Physica A: Statistical Mechanics and its Applications 389 (13), 2545-2556, 2010 | 10 | 2010 |
| Attribution markers and data mining in art authentication BI Łydżba-Kopczyńska, J Szwabiński Molecules 27 (1), 70, 2021 | 8 | 2021 |
| Dynamics of three types of annual plants competing for water and light A Pȩkalski, J Szwabiński Physica A: Statistical Mechanics and its Applications 392 (4), 710-721, 2013 | 7 | 2013 |
Tomasz WeronFaculty of Pure and Applied Mathematics, Wroclaw University of Science and Technology在 pwr.edu.pl 的电子邮件经过验证
