| Tunable magnetoelastic phononic crystals JF Robillard, OB Matar, JO Vasseur, PA Deymier, M Stippinger, ... Applied Physics Letters 95 (12), 124104, 2009 | 246 | 2009 |
| Enhancing resilience of interdependent networks by healing M Stippinger, J Kertész Physica A: Statistical Mechanics and its Applications 416, 481-487, 2014 | 67 | 2014 |
| Stimulus complexity shapes response correlations in primary visual cortex GO Mihály Bányai, Andreea Lazar, Liane Klein, Johanna Klon-Lipok, Marcell ... Proceedings of the National Academy of Sciences 116 (7), 2723-2732, 2019 | 56 | 2019 |
| Hybrid phase transition into an absorbing state: Percolation and avalanches D Lee, S Choi, M Stippinger, J Kertész, B Kahng Physical Review E 93 (4), 042109, 2016 | 55 | 2016 |
| Complete inference of causal relations between dynamical systems Z Benkő, A Zlatniczki, M Stippinger, D Fabó, A Sólyom, L Erőss, A Telcs, ... arXiv preprint arXiv:1808.10806, 2018 | 18 | 2018 |
| Universality and scaling laws in the cascading failure model with healing M Stippinger, J Kertész Physical Review E 98 (4), 042303, 2018 | 7 | 2018 |
| Manifold-adaptive dimension estimation revisited Z Benkő, M Stippinger, R Rehus, A Bencze, D Fabó, B Hajnal, LG Eröss, ... PeerJ Computer Science 8, e790, 2022 | 6 | 2022 |
| Causal Discovery of Stochastic Dynamical Systems: A Markov Chain Approach M Stippinger, A Bencze, Á Zlatniczki, Z Somogyvári, A Telcs Mathematics 11 (4), 852, 2023 | 5 | 2023 |
| Bayesian inference of causal relations between dynamical systems Z Benkő, Á Zlatniczki, M Stippinger, D Fabó, A Sólyom, L Erőss, A Telcs, ... Chaos, Solitons & Fractals 185, 115142, 2024 | 4 | 2024 |
| BiometricBlender: Ultra-high dimensional, multi-class synthetic data generator to imitate biometric feature space M Stippinger, D Hanák, MT Kurbucz, G Hanczár, OM Törteli, ... SoftwareX 22, 101366, 2023 | 4 | 2023 |
| Analytic results and weighted Monte Carlo simulations for CDO pricing M Stippinger, É Rácz, B Vető, Z Bihary The European Physical Journal B 85 (2), 1-11, 2012 | 4 | 2012 |
| CCDH: Complexity based Causal Discovery of Hidden common cause in time series M Stippinger, B Varga, Z Benkő, D Fabó, L Erőss, Z Somogyvári, A Telcs Chaos, Solitons & Fractals 176, 114054, 2023 | 3 | 2023 |
| Relaxation of Some Confusions about Confounders Á Zlatniczki, M Stippinger, Z Benkő, Z Somogyvári, A Telcs Entropy 23 (11), 1450, 2021 | 2 | 2021 |
| Feature space reduction method for ultrahigh-dimensional, multiclass data: Random forest-based multiround screening (RFMS) G Hanczár, M Stippinger, D Hanák, MT Kurbucz, OM Törteli, Á Chripkó, ... arXiv preprint arXiv:2305.15793, 2023 | 1 | 2023 |
| Feature space reduction method for ultrahigh-dimensional, multiclass data: random forest-based multiround screening (RFMS) G Hanczár, M Stippinger, D Hanák, MT Kurbucz, OM Törteli, Á Chripkó, ... Machine Learning: Science and Technology 4 (4), 045012, 2023 | 1 | 2023 |
| Inferring causal relations between neurophysiological signals with dimensional causality Z Benkő, M Stippinger, Á Zlatnicki, D Fabó, A Sólyom, L Erőss, ... IBRO Reports 6, S135, 2019 | 1 | 2019 |
| COMPLETE INFERENCE OF CAUSAL RELATIONS: VALIDATION OF THE DIMENSIONAL CAUSALITY ANALYSIS METHOD ON EVOKED EPILEPTIC ACTIVITY IN VITRO Z Somogyvári, M Stippinger, Z Benkő, Á Zlatniczky, A Bencze, ... IBRO Neuroscience Reports 15, S800, 2023 | | 2023 |
| The contribution of response correlations to the neural code of V1 M Bányai, M Stippinger, D Szalai, G Orbán, A Lazar, L Klein, J Klon-Lipok, ... Conference on Cognitive Computational Neuroscience (CCN 2018), 1-4, 2018 | | 2018 |
| Computational study of collective breakdown phenomena M Stippinger Fizikai Tudományok Doktori Iskola, 2017 | | 2017 |
| Enhancing resilience of interdependent networks M Stippinger, J Kertész organised by the Doctoral School of Physics of the Faculty of Natural …, 2013 | | 2013 |
Zoltán SomogyváriWigner Research Centre for PhysicsVerified email at wigner.hu
