Jelasity M.  1997.  A Wave Analysis of the Subset Sum Problem. ICGA. :89–96.

Jelasity M.  1998.  UEGO, an Abstract Niching Technique for Global Optimization. PPSN. 1498:378–387.

Jelasity M, Ortigosa PMartínez, García I.  2001.  UEGO, an Abstract Clustering Technique for Multimodal Global Optimization. Journal of Heuristics. 7:215–233.

Ortigosa P.M, García I., Jelásity M..  2001.  Two Approaches for Parallelizing the UEGO Algorithm. Optimization Theory: Recent Developments from Mátraháza. :159–177.

Jelasity M.  2000.  Towards Automatic Domain Knowledge Extraction for Evolutionary Heuristics. Parallel Problem Solving from Nature PPSN VI. :755–764.

Tóth L, Nagy B, Janthó D, Vidács L, Gyimóthy T.  2019.  Towards an Accurate Prediction of the Question Quality at Stack Overflow Using a Deep-Learning-Based NLP Approach. Proceedings of ICSOFT 2019, 14th International Conference on Software Technologies. :631-639.

Csirik J, Johnson DS, Kenyon C, Orlin JB, Shor PW, Weber RR.  2000.  On the Sum-of-squares Algorithm for Bin Packing. Proceedings of the Thirty-second Annual ACM Symposium on Theory of Computing. :208–217.

Szabó Z, Téglás K, Berta Á, Jelasity M, Bilicki V.  2019.  Stunner: A Smart Phone Trace for Developing Decentralized Edge Systems. Distributed Applications and Interoperable Systems. :108–115.

Jelasity M.  2001.  The shape of evolutionary search : discovering and representing search space structure.

Kocsor A, A., Jr. K, László T, Márk J, László F, Tibor G, János C.  1999.  A Segment-Based Statistical Speech Recognition System for Isolated/Continuous Number Recognition. Proceedings of the 6th Fenno-Ugric Symposium on Software Technology (FUSST'99). :201-211.

Jelasity M., Press M., Paechter B..  2002.  A scalable and robust framework for distributed applications. Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600). 2:1540-1545vol.2.

Danner G, Jelasity. M.  2018.  Robust decentralized mean estimation with limited communication. Lecture Notes in Computer Science. 11014 :447–461.

Ortigosa PM, García I., Jelasity M.  2001.  Reliability and Performance of UEGO, a Clustering-based Global Optimizer. Journal of Global Optimization. 19:265–289.

Tengeri D, Vidács L, Beszédes Á, Jász J, Balogh G, Vancsics B, Gyimóthy T.  2016.  Relating Code Coverage, Mutation Score and Test Suite Reducibility to Defect Density. Proceedings of the 9th IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW'16); The 11th International Workshop on Mutation Analysis (MUTATION'16). :174-179.

Jenei B, Berend G, Varga L.  2019.  Proactive Minimization of Convolutional Networks. 2019 International Joint Conference on Neural Networks (IJCNN). :1-7.

Jelasity M, Preuß M, Eiben A.E.  2002.  Operator Learning for a Problem Class in a Distributed Peer-to-Peer Environment. PPSN. 2439:172–183.

Jelasity M, Preuß M.  2002.  On Obtaining Global Information in a Peer-to-Peer Fully Distributed Environment (Research Note). Euro-Par. 2400:573–577.

Jiang X, Bunke H, Csirik J.  2004.  MEDIAN STRINGS: A REVIEW. Data Mining in Time Series Databases. :173-192.

Jelasity M., PreusB M., Van Steen M., Paechter B..  2002.  Maintaining Connectivity in a Scalable and Robust Distributed Environment. 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID'02). :389-394.

Kiss Á, Jász J, Lehotai G., Gyimóthy T.  2003.  Interprocedural Static Slicing of Binary Executables. Proceedings of the 3rd IEEE International Workshop on Source Code Analysis and Manipulation (SCAM 2003). :118–127.

Toczki J., Gyimóthy T, Jáhni G..  1988.  Implementation of a LOTOS precompiler in PROF-LP. Proceedings of the Fourth Conference of Program Designers. :31-36.

Hegedűs I, Danner G, Jelasity M.  2019.  Gossip Learning as a Decentralized Alternative to Federated Learning. Distributed Applications and Interoperable Systems. :74–90.

Jelasity M., Dombi J..  1995.  Gas, an approach to a solution of the niche radius problem. IEE Conference Publication. :424–429.

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

Jelasity M, Dombi J.  1995.  GAs, a Concept of Modeling Species in Genetic Algorithms. Artificial Evolution. 1063:69–85.