EN HU
logo Tudóstér

Fazekas István

Fazekas István
DE IK
Alkalmazott Matematikai és Valószínűségszámítási Tanszék
egyetemi tanár

Teljes publikációs lista

Tudóstér társszerzők statisztika szűrhető publikációs lista
Feltöltött közlemény:
102
DEA-ban:
77
OA:
28
Publikációs időszak:
1984-2025
2025
1.
Fazekas, I., Fórián, L.: A family of network evolution models with moderate density.
Stat. Pap. 66 (5), 1-18, (cikkazonosító: 105), 2025.
doi DEA WoS
Folyóirat-mutatók:
Q2 Statistics and Probability (2024)
Q2 Statistics, Probability and Uncertainty (2024)
2.
Fazekas, I., Masasila, N. H.: Explicit rate of convergence in strong laws of large numbers for random variables with double indices.
In: The Mediterranean International Conference of Pure & Applied Mathematics and Related Areas : Proceedings book of MICOPAM2025. Szerk.: Mustafa Alkan, Irem Kucukoglu, Ortaç Öneş, et. al, Josip Juraj Strossmayer University of Osijek, Osijek, 200, 2025. ISBN: 9789534691502
DEA
3.
Fazekas, I., Fazekas, B., Suja, M. O.: Limit theorems for runs containing two types of contaminations.
Period. Math. Hung. 90 (1), 78-93, 2025.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q3 Mathematics (miscellaneous) (2024)
4.
Fazekas, I., Fazekas, B., Fórián, L.: On the Convergence Rate for the Longest at Most T-Contaminated Runs of Heads.
Entropy. 27 (1), 1-9, (cikkazonosító: 33), 2025.
doi DEA
Folyóirat-mutatók:
Q2 Electrical and Electronic Engineering (2024)
Q2 Information Systems (2024)
Q2 Mathematical Physics (2024)
Q2 Physics and Astronomy (miscellaneous) (2024)
5.
Fazekas, I., Masasila, N. H.: Quantitative strong laws of large numbers for random variables with double indices.
Ann. Math. Inform. 62, 55-65, 2025.
doi DEA WoS
Folyóirat-mutatók:
Q4 Computer Science (miscellaneous) (2024)
Q4 Mathematics (miscellaneous) (2024)
2024
6.
Fazekas, I., Barta, A., Fórián, L., Porvázsnyik, B.: A continuous-time network evolution model describing N-interactions.
MATH. 9 (12), 35721-35742, 2024.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q2 Mathematics (miscellaneous)
7.
Fazekas, I., Masasila, N. H.: A general approach to conditional strong laws of large numbers.
Annales Universitat. Mariae Curie-Sklodowska, A - Math. 78 (1), 27-35, 2024.
doi DEA Scopus
Folyóirat-mutatók:
Q4 Applied Mathematics
Q4 Algebra and Number Theory
Q4 Analysis
Q4 Statistics and Probability
8.
Fazekas, I., Fazekas, B., Suja, M. O.: A limit theorem for runs containing two types of contaminations.
Period. Math. Hung. 90 (1), 78-93, 2024.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q3 Mathematics (miscellaneous)
9.
Fazekas, I., Fazekas, B., Suja, M. O.: Convergence rate for the longest T-contaminated runs of heads.
Stat. Probab. Lett. 208, 1-8, 2024.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q2 Statistics and Probability
Q3 Statistics, Probability and Uncertainty
2023
10.
Fazekas, I., Barta, A., Noszály, C., Porvázsnyik, B.: A continuous-time network evolution model describing 3-interactions.
Commun. Stat.-Theory Methods. 52 (11), 4001-4020, 2023.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q3 Statistics and Probability
11.
Fazekas, I., Fórián, L., Barta, A.: Deep Learning from Noisy Labels with Some Adjustments of a Recent Method.
Infocommun. J. 15 (Special), 9-12, 2023.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q3 Computer Science (miscellaneous)
Q3 Electrical and Electronic Engineering
2022
12.
Fazekas, I.: 2022 IEEE 2nd Conference on Information Technology and Data Science (CITDS): Proceedings: May 16-18, 2022. : Online on CISCO Webex platform.
Institute of Electrical and Electronics Engineers (IEEE), Piscataway, 337 p., 2022. ISBN: 9781665496537
DEA
13.
Čuprunov, A., Fazekas, I.: On the Numbers of Particles in Cells in an Allocation Scheme Having an Even Number of Particles in Each Cell.
Mathematics. 10, 1-22, 2022.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q2 Computer Science (miscellaneous)
Q2 Engineering (miscellaneous)
Q2 Mathematics (miscellaneous)
2021
14.
Fazekas, I., Barta, A.: A Continuous-Time Network Evolution Model Describing 2- and 3-Interactions.
Mathematics. 9 (23), 1-26, (cikkazonosító: 3143), 2021.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q2 Computer Science (miscellaneous)
Q2 Engineering (miscellaneous)
Q2 Mathematics (miscellaneous)
15.
Fazekas, I., Barta, A., Fórián, L.: Ensemble noisy label detection on MNIST.
Ann. Math. Inform. 53, 125-137, 2021.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q3 Computer Science (miscellaneous)
Q4 Mathematics (miscellaneous)
16.
Fazekas, I., Suja, M. O.: Limit theorems for contaminated runs of heads.
Ann. Univ. Sci. Budapest, Sect. Comp. 52, 131-146, 2021.
DEA
17.
Fazekas, I., Barta, A.: Theoretical and simulation results for a 2-type network evolution model.
In: Proceedings of the 1st Conference on Information Technology and Data Science. Ed.: István Fazekas, András Hajdu, Tibor Tómács, CEUR Workshop Proceedings, Debrecen, 104-114, 2021, (CEUR Workshop Proceedings, ISSN 1613-0073 ; 2874.)
DEA Scopus
2020
18.
Fazekas, I., Pecsora, S.: Numerical results on noisy blown-up matrices.
Ann. Math. Inform. 51, 17-28, 2020.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q4 Computer Science (miscellaneous)
Q4 Mathematics (miscellaneous)
19.
Čuprunov, A., Fazekas, I.: On the number of empty cells in the allocation scheme of indistinguishable particles.
Annales Universitatis Mariae Curie-Sklodowska A Math. 74 (1), 15-29, 2020.
doi DEA
20.
Fazekas, I., Pecsora, S.: On the spectrum of noisy blown-up matrices.
Special Matrices. 8 (1), 104-122, 2020.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q2 Algebra and Number Theory
Q2 Geometry and Topology
21.
Fazekas, I., Barta, A., Noszály, C.: Simulation results on a triangle-based network evolution model.
Ann. Math. Inform. 51, 7-15, 2020.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q4 Computer Science (miscellaneous)
Q4 Mathematics (miscellaneous)
2019
22.
Čuprunov, A., Fazekas, I.: Poisson limit theorems for the generalized allocation scheme.
Ann. Univ. Sci. Budapest, Sect. Comp. 49, 77-96, 2019.
DEA
23.
Fazekas, I., Noszály, C., Uzonyi, N.: Taylor's power law for the N-stars network evolution model.
Mod. Stoch.: Theory App. 6 (3), 311-331, 2019.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q3 Modeling and Simulation
Q4 Statistics and Probability
Q3 Statistics, Probability and Uncertainty
24.
Fazekas, I., Noszály, C., Perecsényi, A.: The N-star network evolution model.
J. Appl. Probab. 56 (2), 416-440, 2019.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q2 Mathematics (miscellaneous)
Q2 Statistics and Probability
Q3 Statistics, Probability and Uncertainty
2018
25.
Fazekas, I., Noszály, C., Perecsényi, A.: A population evolution model and its applications to random networks.
Stat. Probab. Lett. 143, 17-27, 2018.
doi DEA WoS Scopus
Folyóirat-mutatók:
Q3 Statistics and Probability
Q3 Statistics, Probability and Uncertainty
DEENK Debreceni Egyetem
© 2012 Debreceni Egyetem
Ez a weboldal sütiket használ. Az Uniós törvények értelmében kérem, engedélyezze a sütik használatát, vagy zárja be az oldalt.