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Zsigmond Benkő
Zsigmond Benkő
Wigner Research Centre for Physics
Verified email at wigner.hu - Homepage
Title
Cited by
Cited by
Year
Characterization of connexin36 gap junctions in the human outer retina
O Kántor, Z Benkő, A Énzsöly, C Dávid, A Naumann, R Nitschke, A Szabó, ...
Brain Structure and Function 221 (6), 2963-2984, 2016
392016
Exact Inference of Causal Relations in Dynamical Systems
Z Benkő, Á Zlatniczki, D Fabó, A Sólyom, L Erőss, A Telcs, Z Somogyvári
arXiv preprint arXiv:1808.10806, 2018
25*2018
Strategic positioning of Connexin36 Gap junctions across human retinal ganglion cell dendritic arbors
O Kántor, G Szarka, Z Benkő, Z Somogyvári, E Pálfi, G Baksa, G Rácz, ...
Frontiers in cellular neuroscience, 409, 2018
142018
Model-free detection of unique events in time series
Z Benkő, T Bábel, Z Somogyvári
Scientific reports 12 (1), 1-17, 2022
122022
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
82022
Causal relationship between local field potential and intrinsic optical signal in epileptiform activity in vitro
Z Benkő, K Moldován, K Szádeczky-Kardoss, L Zalányi, S Borbély, I Világi, ...
Scientific reports 9 (1), 1-12, 2019
72019
How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time series
Z Benkő, T Bábel, Z Somogyvári
arXiv preprint arXiv:2004.11468, 2020
52020
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
22023
Time Series and Interactions: Data Processing in Epilepsy Research
Z Benkő, D Fabó, Z Somogyvári
Computational Neurology and Psychiatry, 73-91, 2017
22017
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
12024
Relaxation of Some Confusions about Confounders
Á Zlatniczki, M Stippinger, Z Benkő, Z Somogyvári, A Telcs
Entropy 23 (11), 1450, 2021
12021
Reconstructing shared dynamics with a deep neural network
Z Benkő, Z Somogyvári
arXiv preprint arXiv:2105.02322, 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
Detecting Causality in the Frequency Domain with Cross-Mapping Coherence
Z Benkő, B Varga, M Stippinger, Z Somogyvári
arXiv preprint arXiv:2407.20694, 2024
2024
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
Reconstructing common latent input from time series with the mapper-coach network and error backpropagation
Z Benkő, Z Somogyvári
arXiv preprint arXiv:2105.02322, 2021
2021
FROM CLUSTERING TO CAUSALITY ANALYSIS: APPLICATION AND DEVELOPMENT OF SIGNAL PROCESSING METHODS IN A NEUROSCIENCE CONTEXT
Z Benkő
2021
Ccdh: Complexity Based Causal Discovery of Hidden Common Cause (and Other Beasts) in Time Series
B Varga, M Stippinger, Z Benkő, D Fabó, P Halász, L Erőss, Z Somogyvári, ...
Available at SSRN 4294786, 0
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