Jelasity M, Dombi J.  1998.  GAS, A Concept on Modeling Species in Genetic Algorithms. Artif. Intell.. 99:1–19.

Quatrehomme G, Cotin S, Subsol G, Delingette H, Garidel Y, Grévin G, Fidrich M, Bailet P, Ollier A.  1997.  A Fully Three-Dimensional Method for Facial Reconstruction Based on Deformable Models. Journal of Forensic Sciences. 42:649-652.

Sloan RH, Takata K, Turán G.  1998.  On Frequent Sets of Boolean Matrices. Ann. Math. Artif. Intell.. 24:193–209.

Gosztolya G, Tóth L.  2018.  A feature selection-based speaker clustering method for paralinguistic tasks. Pattern Analysis and Applications. 21:193–204.

Kicsi A, Csuvik V, Vidács L, Horváth F, Beszédes Á, Gyimóthy T, Kocsis F.  2019.  Feature Analysis using Information Retrieval, Community Detection and Structural Analysis Methods in Product Line Adoption. Journal of Systems and Software. 155:70-90.

Csirik J, Kellerer H, Woeginger GJ.  1992.  The exact LPT-bound for maximizing the minimum completion time. Oper. Res. Lett.. 11:281–287.

Gábor S, Gábor A, Nagy C, Ferenc R, Gyimóthy T.  2017.  Empirical Study on Refactoring Large-scale Industrial Systems and Its Effects on Maintainability. Journal of Systems and Software. 129:107–126.

Hegedüs P, Kádár I, Ferenc R, Gyimóthy T.  2018.  Empirical evaluation of software maintainability based on a manually validated refactoring dataset. Information and Software Technology. 95:313-327.

Berend G.  2020.  Efficient algorithm to compute Markov transitional probabilities for a desired PageRank. EPJ Data Science. 9:23.

Jiang X., Abegglen K., Bunke H., Csirik J.  2003.  Dynamic Computation of Generalised Median Strings. Pattern Anal. Appl.. 6:185–193.

Jiang X., Abegglen K., Bunke H., Csirik J.  2003.  Dynamic computation of generalised median strings. Pattern Analysis & Applications. 6:185–193.

Gosztolya G, Tóth L.  2017.  DNN-based Feature Extraction for Conflict Intensity Estimation from Speech. IEEE Signal Processing Letters. 24:1837–1841.

Gergely T, Balogh G, Horvath F, Vancsics B, Beszedes A, Gyimothy T.  2019.  Differences between a static and a dynamic test-to-code traceability recovery method. SOFTWARE QUALITY JOURNAL. 27:797-822.

Ferenc R, Viszkok T, Aladics T, Jász J, Hegedűs P.  2020.  Deep-water framework: The Swiss army knife of humans working with machine learning models. SoftwareX. 12:100551.

Blázsik Z., Holló C., Imreh B..  1998.  On Decision-mappings Related to Process Network Synthesis Problem. Acta Cybern.. 13:319–328.

Szilágyi G., Harmath L., Gyimóthy T..  2001.  The Debug slicing of logic programs. Acta Cybernetica. 15:257–278.

Faragó C, Hegedüs P, Végh ÁZoltán, Ferenc R.  2014.  Connection Between Version Control Operations and Quality Change of the Source Code. {Acta Cybernetica}. 21:585–607.

Turán G, Vatan F.  1997.  On the Computation of Boolean Functions by Analog Circuits of Bounded Fan-In. J. Comput. Syst. Sci.. 54:199–212.

Turán G.  1995.  On the Complexity of Planar Boolean Circuits. Computational Complexity. 5:24–42.

Kocsor A, Tóth L, Kuba, Jr. A, Kovács K, Jelasity M, Gyimóthy T, Csirik J.  2000.  A Comparative Study of Several Feature Space Transformation and Learning Methods for Phoneme Classification. International Journal of Speech Technology. 2:263-276.

Faigle U, Schrader R, Turán G.  1992.  The Communication Complexity of Interval Orders. Discrete Applied Mathematics. 40:19–28.

Vidács L, Beszédes Á, Gyimóthy T.  2009.  Combining preprocessor slicing with C/C++ language slicing. Science of Computer Programming. 74:399-413.

Horváth F, Gergely T, Beszédes Á, Tengeri D, Balogh G, Gyimóthy T.  2017.  Code Coverage Differences of Java Bytecode and Source Code Instrumentation Tools. Software Quality Journal.

Horvath F, Gergely T, Beszedes A, Tengeri D, Balogh G, Gyimothy T.  2019.  Code coverage differences of Java bytecode and source code instrumentation tools. SOFTWARE QUALITY JOURNAL. 27:79-123.

Gosztolya G, Busa-Fekete R.  2019.  Calibrating AdaBoost for Phoneme Classification. Soft Computing. 23:115–128.