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Marcell Stippinger
Marcell Stippinger
Wigner Research Centre for Physics
Verified email at wigner.hu - Homepage
Title
Cited by
Cited by
Year
Tunable magnetoelastic phononic crystals
JF Robillard, OB Matar, JO Vasseur, PA Deymier, M Stippinger, ...
Applied Physics Letters 95 (12), 124104, 2009
2342009
Enhancing resilience of interdependent networks by healing
M Stippinger, J Kertész
Physica A: Statistical Mechanics and its Applications 416, 481-487, 2014
612014
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
502019
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
482016
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
142018
Universality and scaling laws in the cascading failure model with healing
M Stippinger, J Kertész
Physical Review E 98 (4), 042303, 2018
72018
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
62022
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
42012
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
22023
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
12023
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
12023
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
12023
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
12023
Relaxation of Some Confusions about Confounders
Á Zlatniczki, M Stippinger, Z Benkő, Z Somogyvári, A Telcs
Entropy 23 (11), 1450, 2021
12021
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
12019
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
Efficient pricing of CDO contracts using compound Poisson model
M Stippinger, J Kertész
2010
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