Publications of Igor Farkaš

  • Pócoš Š., Bečková I., Farkaš I.: RecViT: Enhancing Vision Transformer with Top-Down Information Flow. In 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. 2024.pdfbib
  • Pecháč M., Chovanec M., Farkaš I.: Self-supervised network distillation: An effective approach to exploration in sparse reward environments. Neurocomputing 2024.pdfbib
  • Farkaš I., Lúčny A., Vavrečka M.: Approaches to generating arm movements in humanoid robot NICO. In Cognition and Artificial Life, Flow, z.s.. 57-58. 2024.pdfbib
  • Cibula M., Kerzel M., Farkaš I.: Learning Low-Level Causal Relations using a Simulated Robotic Arm. In International Conference on Artificial Neural Networks (ICANN), Springer. 285-298. 2024.pdfbib
  • Pecháč M., Chovanec M., Farkaš I.: Self-supervised network distillation: an effective approach to exploration in sparse reward environments. Technical report. . 2023. arXiv:2302.11563 [cs.AI].pdfbib
  • Lúčny A., Malinovská K., Farkaš I.: Robot at the Mirror: Learning to Imitate via Associating Self-supervised Models. In Artificial Neural Networks and Machine Learning – ICANN, Springer Nature Switzerland AG. 471-482. 2023.pdfbib
  • Kovač L., Farkaš I.: Safe Reinforcement Learning in a Simulated Robotic Arm. In Artificial Neural Networks and Machine Learning – ICANN, Springer Nature Switzerland AG. 585-589. 2023.pdfbib
  • Farkaš I.: Dôveryhodnost’ výpočtových modelov v umelej inteligencii a robotike. In Kognícia a umelý život XXI, Smolenice, Vydavateľstvo UK v Bratislave. 28-29. 2023.pdfbib
  • Farkaš, I., Ballová Mikušková, E., Takáč, M., Malinovská, K., Fandl, M.: Kognícia a umelý život 2023. Univerzita Komenského v Bratislave. 2023.pdfbib
  • Herashchenko D., Farkaš I.: Appearance-based gaze estimation enhanced with synthetic images using deep neural networks. In IEEE Symposium Series on Computational Intelligence (SSCI). 129-134. 2023.pdfbib
  • Reinboth T., Farkaš I.: Ultimate grounding of abstract concepts: A graded account. Journal of Cognition, 5(1). 2022.pdfbib
  • Farkaš I., Cimrová B., Pócoš Š., Bečková I.: Pozornost’ ako biologicky inšpirovaný koncept pre vysvetlitel’né, robustné a efektı́vne strojové učenie. In Šejnová G., Vavrečka M., Hvorecký J. (eds.), Kognice a umělý život 2022, ČVUT v Praze. 34-38. 2022.pdfbib
  • Bečková I., Pócoš Š., Farkaš I.: Skúmanie vzdialenostı́ adverzariálnych vstupov k jednotlivým triedam v hlbokých neurónových siet’ach. In Šejnová G., Vavrečka M., Hvorecký J. (eds.), Kognice a umělý život 2022, ČVUT v Praze. 160-161. 2022.pdfbib
  • Pecháč M., Farkaš I.: Intrinsic motivation based on feature extractor distillation. In Šejnová G., Vavrečka M., Hvorecký J. (eds.), Kognice a umělý život 2022, ČVUT v Praze. 84-90. 2022.pdfbib
  • Malinovská K., Farkaš I., Harvanová J., Hoffmann M.: A connectionist model of associating proprioceptive and tactile modalities in a humanoid robot. In IEEE International Conference on Development and Learning (ICDL). 2022.pdfbib
  • Pócoš Š., Bečková I., Farkaš I.: Examining the Proximity of Adversarial Examples to Class Manifolds in Deep Networks. In International Conference on Artificial Neural Networks (ICANN), Springer. 645-656. 2022.pdfbib
  • Cimrová B., Marko M., Farkaš I., Sobota B., Korečko Š., Rošťáková Z., Rosipal R.: Tréning kapacity vizuálnej pracovnej pamäti v prostredí virtuálnej reality. In Šejnová G., Vavrečka M., Hvorecký J. (eds.) (eds.), Kognice a umělý život XX, České vysoké učení technické v Praze. 23-27. 2022.pdfbib
  • Holas J., Farkaš I.: Advances in Adaptive Skill Acquisition. In Artificial Neural Networks and Machine Learning - ICANN 2021, Springer Nature Switzerland AG. 650-661. 2021.pdfbib
  • Pecháč M., Farkaš I.: Intrinsic Motivation Model Based on Reward Gating. In Artificial Neural Networks and Machine Learning - ICANN 2021, Springer Nature Switzerland AG. 688-699. 2021.pdfbib
  • Malinovská K., Farkaš I.: Generative properties of Universal Bidirectional Activation-based Learning. In Artificial Neural Networks and Machine Learning - ICANN 2021, Springer Nature Switzerland AG. 80-83. 2021.pdfbib
  • Šejnová G., Mendrechová M., Otahal M., Sokovnin N., Farkaš I., Vavrečka M.: Reward redistribution for reinforcement learning of dynamic nonprehensile manipulation. In International Conference on Control, Automation and Robotics. 326-331. 2021.pdfbib
  • Pócoš Š., Bečková I., Kuzma T., Farkaš I.: Assessment of manifold unfolding in trained deep neural network classifiers. In Trustworthy AI - Integrating Learning, Optimization and Reasoning, Springer Nature Switzerland AG. 2021.pdfbib
  • Holas J., Farkaš I.: Adaptive skill acquisition in hierarchical reinforcement learning. In Artificial Neural Networks and Machine Learning - ICANN 2020, Springer Nature Switzerland AG. 383-394. 2020.pdfbib
  • Bečková I., Pócoš Š., Farkaš I.: Computational analysis of robustness in neural network classifiers. In Artificial Neural Networks and Machine Learning - ICANN 2020, Springer Nature Switzerland AG. 65-76. 2020.pdfbib
  • Farkaš I., Masulli P., Wermter S. (eds.): Artificial Neural Networks and Machine Learning - ICANN 2020, part I. Springer Nature Switzerland AG. 2020.pdfbib
  • Farkaš I., Masulli P., Wermter S. (eds.): Artificial Neural Networks and Machine Learning - ICANN 2020, part II. Springer Nature Switzerland AG. 2020.pdfbib
  • Rosipal R., Porubcová N., Barančok P. , Cimrová B., Farkaš I., Trejo L.J.: Effects of mirror-box therapy on modulation of sensorimotor EEG oscillatory rhythms: A single-case longitudinal study. Journal of Neurophysiology 2019.pdfbib
  • Pospı́chal J., Farkaš I., Pecháč M., Malinovská K.: Modeling self-organized emergence of perspective in/variant mirror neurons in a robotic system. In Proceedings of the 2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob). 2019.pdfbib
  • Gergeľ P., Farkaš I.: Echo state networks with artificial astrocytes and hebbian connections. In 15th International Work-Conference on Artificial Neural Networks, Springer. 457-466. 2019.pdfbib
  • Kuzma T., Farkaš I.: Embedding complexity of learned representations in neural networks. In 28th International Conference on Artificial Neural Networks (ICANN), vol. 2. 518-528. 2019.pdfbib
  • Farkaš I., Takáč M, Gergeľ P., Tomko M. (eds.): Kognícia a umelý život XIX. Univerzita Komenského v Bratislave. 2019.pdfbib
  • Korečko Š., Sobota B., Hudák M., Farkaš I., Cimrová B., Vasiľ P., Trojčák D.: Experimental procedure for evaluation of visuospatial cognitive functions training in virtual reality. In Proceedings of the International Conference on Advanced Intelligent Systems and Informatics (AISI). 643-652. 2019.pdfbib
  • Malinovská, K., Malinovský, Ľ., Krsek, P., Kraus, S., Farkaš, I.: UBAL: a Universal Bidirectional Activation-based Learning Rule for Neural Networks. In CIIS 2019: Proceedings of the 2019 International Conference on Computational Intelligence and Intelligent Systems, Association for Computing Machinery, New York, NY, USA. 2019.pdfbib
  • Hoffmann M., Straka Z., Farkaš I., Vavrečka M., Metta G.: Robotic homunculus: Learning of artificial skin representation in a humanoid robot motivated by primary somatosensory cortex. IEEE Transactions on Cognitive and Developmental Systems 10(2). 163-176. 2018.pdfbib
  • Jug J., Kolenik T., Ofner A., Farkaš I.: Computational model of enactive visuospatial mental imagery using saccadic perceptual actions. Cognitive Systems Research 49, 157-177. 2018.pdfbib
  • Malinovská, K., Malinovský, Ľ, Farkaš, I.: UBAL: Univerzálny biologicky-motivovaný algoritmus s lokálnym pravidlom. In Šašinka et al. (eds.), Kognice a umělý život XVIII, Flow, z.s., Brno. 50-52. 2018.pdfbib
  • Tuna, M, Malinovská, K., Farkaš, I.: Kategorické Siamské siete. In Šašinka et al. (eds.), Kognice a umělý život XVIII, Flow, z.s., Brno. 80-81. 2018.bib
  • Kuzma T., Farkaš I.: Computational analysis of learned representations in deep neural network classifiers. In International Joint Conference on Neural Networks, IEEE, Rio de Janeiro. 4420-4425. 2018.pdfbib
  • Torda M,, Farkaš I.: Evaluation of information-theoretic measures in echo state networks on the edge of stability. In International Joint Conference on Neural Networks, IEEE, Rio de Janeiro. 117-122. 2018.pdfbib
  • Korečko Š., Hudák M., Sobota S., Marko M., Cimrová B., Farkaš I., Rosipal R.: Assessment and training of visuospatial cognitive functions in virtual reality: proposal and perspective. In Proceedings of 9th IEEE International Conference on Cognitive Infocommunications (CogInfoCom) . 39-43. 2018.pdfbib
  • Cimrová B., Rošťáková Z., Varga Doležalová M., Farkaš I., Rosipal R.: Hľadanie súvislostí medzi charakteristikami spánku a kognitívnym výkonom pacientov s ložiskovou ischémiou mozgu. In Kognice a umělý život XVIII, Flow, z.s. , Brno. 11-12. 2018.pdfbib
  • Gergeľ P. and Farkaš I.: Investigating the role of astrocyte units in a feedforward neural network. In International Conference on Artificial Neural Networks. 73--83. 2018.pdfbib
  • Jug J., Kolenik T., Ofner A., Farkaš I.: Výpočtový model enaktívnej vizuálno-priestorovej mentálnej predstavivosti. In Šašinka et al. (eds.), Kognice a umělý život XVIII, Flow, z.s.. 31-32. 2018.bib
  • Malinovská K., Malinovský Ľ., Farkaš I.: Towards more biologically plausible error-driven learning for artificial neural networks. In Artificial Neural Networks and Machine Learning (ICANN 2018), Springer. 228-231. 2018.pdfbib
  • Farkaš I., Gergeľ P.: Maximizing memory capacity of echo state networks with orthogonalized reservoirs. In International Joint Conference on Neural Networks, IEEE. 2437-2442. 2017.pdfbib
  • Farkaš I.: On abstraction: psychological, neural, and computational perspectives. In Kognice a umělý život (KUZ). 2016.pdfbib
  • Rybár J., Cimrová B., Farkaš I., Varga Doležalová M., Rosipal R.: Špecifiká kognitívneho výkonu pacientov po ložiskovej ischémii mozgu. In Kognice a umělý život (KUZ). 2016.pdfbib
  • Farkaš I., Bosák R., Gergeľ P.: Computational analysis of memory capacity in echo state networks. Neural Networks 83, 109-120. 2016.pdfbib
  • Csiba P., and Farkaš I.: Computational analysis of the bidirectional activation-based learning in autoencoder task. In The International Joint Conference on Neural Networks (IJCNN), Killarney, Ireland. 2015.pdfbib
  • Rosipal R., Cimrová B., Rückschloss L., Kohút Z., Farkaš I., Porubcová N.: Vplyv zrkadlového tréningu na moduláciu motorických rytmov: elektrofyziologická a klinická štúdia pacienta s hemiparézou po mozgovom infarkte. In Kognícia a umelý život XV, Vydavateľstvo Univerzity Komenského, Bratislava. 152-157. 2015.pdfbib
  • Kuzma T., Farkaš I.: Automatická tvorba učebných plánov pre strojové učenie. In Kognícia a umelý život XV, Vydavateľstvo Univerzity Komenského, Bratislava. 99-102. 2015.pdfbib
  • Farkaš, I., Takáč, M., Rybár, J., Kelemen, J. (eds.): Kognícia a umelý život XV. Univerzita Komenského v Bratislave, Bratislava. 2015.pdfbib
  • Gergeľ P., Farkaš I.: Connectionist modeling of part–whole analogy learning. In Proceedings of the EuroAsianPacific Joint Conference on Cognitive Science. 587-592. 2015.pdfbib
  • Vavrečka M., Farkaš I.: A multimodal connectionist architecture for unsupervised grounding of spatial language. Cognitive Computation 6:101-112. 2014.pdfbib
  • Farkaš I., Cimrová B., Rybár J.: Potlačenie motorických rytmov v mozgu pri pozorovaní pohybu. In Kognitivní věda a umělý život II, Slezská univerzita v Opave. 67-74. 2014.pdfbib
  • Cimrová B., Farkaš I., Rosipal R.: Využitie rozhrania mozog–počítač pri neurorehabilitácii: prehľad aktuálneho výskumu. In Kognitivní věda a umělý život II, Slezská univerzita v Opave. 33-38. 2014.pdfbib
  • Švec M., Farkaš I.: Calculation of object position in various reference frames with a robotic simulator. In Proceedings of the 36th Annual Conference of the Cognitive Science Society . 2014.pdfbib
  • Barančok P., Farkaš I.: Memory capacity of input-driven echo state networks at the edge of chaos. In Proceedings of the International Conference on Artificial Neural Networks (ICANN). 41-48. 2014.pdfbib
  • Farkaš I.: Je reprezentačný pluralizmus v kognitívnej vede nevyhnutný?. In Kelemen J., Rybár J., Farkaš I., Takáč M. (eds.), Kognitivní věda a umělý život, Slezská univerzita v Opavě. 107-114. 2013.pdfbib
  • Rebrová K., Farkaš I.: Robotický model systému zrkadliacich neurónov: experimentálna analýza. In Kelemen J., Rybár J., Farkaš I., Takáč M. (eds.), Kognitivní věda a umělý život, Slezská univerzita v Opavě. 223-230. 2013.pdfbib
  • Farkaš I., Rebrová K.: Bidirectional activation-based neural network learning algorithm. In Proceedings of the International Conference on Artificial Neural Networks (ICANN), Springer. 154-161. 2013.pdfbib
  • Rebrová K., Pecháč M., Farkaš I.: Towards a robotic model of the mirror neuron system. In International Conference on Development and Learning and on Epigenetic Robotics, IEEE. 2013.pdfbib
  • Farkaš I.: Paradigmy a metódy výskumu v kognitívnej vede. In Sborník studijních materiálů ke kurzu Kognitívní věda a umělá inteligence, Gaudeamus, Hradec Králové. 6-21. 2013.pdfbib
  • Farkaš I., Malík T., Rebrová K.: Grounding the meanings in sensorimotor behavior using reinforcement learning. Frontiers in Neurorobotics 6(1). 2012. doi: 10.3389/fnbot.2012.00001.pdfbib
  • Švantner J., Farkaš I., Crocker M.: Modeling utterance-mediated visual attention during situated comprehension. Neural Network World 22(2). 85-101. 2012.pdfbib
  • Rebrová K., Farkaš I.: Robotický model systému zrkadliacich neurónov. In Kelemen J., Nahodil P. (eds.), Kognice a umělý život XII, Slezská univerzita. 231-238. 2012.pdfbib
  • Farkaš I.: Indispensability of computational modeling in cognitive science. Journal of Cognitive Science 13,401-435. 2012.pdfbib
  • Švantner J., Farkaš I., Crocker M.: Modeling utterance-mediated attention in situated language comprehension. In Proceedings of the 33rd Annual Conference of the Cognitive Science Society, Boston, US. 2235-2240. 2011.pdfbib
  • Vavrečka M., Farkaš I.: Unsupervised grounding of spatial relations. In Kokinov B., Karmiloff-Smith A., and Nersessian N. (eds.), Proceedings of the European Conference on Cognitive Science, Sofia, New Bulgarian University Press, Sofia. 2011.pdfbib
  • Rebrová K., Farkaš I.: Neurálne modely v kognitívnej robotike: porozumenie a pomenovávanie akcií. In Kelemen J., Kvasnička V. (eds.), Kognice a umělý život XI, Slezská univerzita, Opava. 231-238. 2011.pdfbib
  • Farkaš I., Malý M., Rebrová K.: Porozumenie motorickým akciám – hypotéza kontinua. In Kelemen J., Kvasnička V. (eds.), Kognice a umělý život XI, Slezská univerzita. 61-68. 2011.pdfbib
  • Farkaš I., Malý M., Rebrová K.: Mirror neurons – theoretical and computational issues. Technical report TR-2011-028. Comenius University in Bratislava. 2011.pdfbib
  • Vavrečka M., Farkaš I., Lhotská L.: Bio-inspired model of spatial cognition. In International Conference on Neural Information Processing (ICONIP). 2011.pdfbib
  • Farkaš I.: Konekcionizmus v náručí výpočtovej kognitívnej vedy. In Kvasnička V. et al. (eds.), Umelá inteligencia a kognitívna veda III. 19-62. 2011.pdfbib
  • Šilar J., Kokoška M., Rebrová K., Farkaš I.: Motor resonance based desynchronization of the EEG mu rhythm. Activitas Nervosa Superior Rediviva 53 2011. Abstract.bib
  • Farkaš I., Malík T.: Connectionist model of action learning and naming (abstract). In IEEE ICDL-EpiRob 2011: IEEE Conference on Development and Learning and Epigenetic Robotics , Frankfurt am Main. 2011.bib
  • Vančo P., Farkaš I.: Experimental comparison of recursive self-organizing maps for processing tree-structured data. Neurocomputing 73 1362-1375. 2010.pdfbib
  • Rakovský M., Schreitter S., Farkaš I.: Affecting sentence comprehension by perceptual or linguistic manipulation. In Presented at CSLD/ESLP 2010, University of California, San Diego, USA. 2010.pdfbib
  • Farkaš I.: Mental causation in a physical brain?. In Brain-Inspired Cognitive Systems, Universidad Politécnica de Madrid. 14-16 July 2010.pdfbib
  • Farkaš I.: Neurálne modely v kognitívnej robotike: vizuálno-motorická interakcia. In Kelemen J., Kvasnička V. (eds.), Kognice a umělý život X, Slezská univerzita, Opava. 93-99. 2010.pdfbib
  • Farkaš I.: Subjektívna skúsenosť očami informatika. Anthropos 7(1). 72-78. 2010.bib
  • Vančo P., Farkaš I.: Recursive self-organizing networks for processing tree structures: Empirical comparison. In International Joint Conference on Computational Intelligence (IJCCI), Madeira, Portugal. 459-466. 2009.pdfbib
  • Farkaš I.: Významy ako mentálne simulácie v situačnom modeli. In Kelemen J., Kvasnička V., Rybár J. (eds.), Kognice a umelý život IX, Slezská univerzita, Opava. 69-76. 2009.pdfbib
  • Bajla I., Rublík F., Arendacká B., Farkaš I., Hornišová K., Štolc S., Witkovský V.: Segmentation and supervised classification of image objects in Epo doping-control. Machine Vision and Applications 20(4). 243-259. 2009.pdfbib
  • Farkaš I.: Learning nonadjacent dependencies with a recurrent neural network. In M. Koeppen et al. (eds.), International Conference on Neural Information Processing Systems (ICONIP'2008), Springer, Lecture Notes in Computer Science. 292-299. 2009.pdfbib
  • Farkaš I., Pokorný M.: Investigating systematicity in the linear RAAM neural network. In Mayor J., Ruh N., Plunkett K. (eds.), Connectionist Models of Behaviour and Cognition, Vol. II, World Scientific, Singapore. 217-228. 2009.pdfbib
  • Švantner J., Farkaš I.: Investigating distributed representations in grammar acquisition with echo state networks. In Proceedings of the Tenth International Conference on Informatics, Elfa, Košice. 265-270. 2009.bib
  • Švantner J., Farkaš I.: Učenie gramatických závislostí pomocou neurónovej siete s echo stavmi. In Kognícia a umelý život IX, Slezská univerzita, Opava. 319-325. 2009.bib
  • Farkaš I., Crocker M.: Syntactic systematicity in sentence processing with a recurrent self-organizing network. Neurocomputing 711172-1179. 2008.pdfbib
  • Farkaš I.: Konceptuálne východiská pre model stelesnenej mysle. In Kvasnička V., Kelemen J., Pospichal J. (eds.), Modely mysle, Vydavateľstvo Európa, Bratislava. 35-64. 2008.pdfbib
  • Šefránek, J., Takáč, M., Farkaš, I.: Vznik inteligencie v umelých systémoch. In Magdolen, D. (eds.), Hmota, život, inteligencia: Vznik, VEDA, Bratislava. 245-270. 2008.pdfbib
  • Farkaš I., Crocker M.: Systematicity in sentence processing with a recursive self-organizing neural network. In M. Verleysen (eds.), Proceedings of the 15th European Symposium on Artificial Neural Networks (ESANN'07), Bruges, Belgium. 49-54. 2007.pdfbib
  • Farkaš I.: Hľadanie kauzálnych vzťahov v probléme mysle a tela z pohľadu neredukcionistického fyzikalizmu. In V. Kvasnička, P. Trebatický, J. Pospichal, J. Kelemen (eds.), Myseľ, inteligencia a život, Vydavateľstvo STU, Bratislava. 3-16. 2007.pdfbib
  • Farkaš I., Vančo P.: Spracovanie postupností symbolov pomocou rekurzívnych neurónových máp. In Kognícia a umelý život VII, Slezská univerzita, Opava. 99-106. 2007.pdfbib
  • Farkaš I., Švantner J.: Učenie nesusedných závislostí pomocou rekurentných neurónových sietí. In Kognícia a umelý život VII, Slezská univerzita, Opava. 389-394. 2007.pdfbib
  • Farkaš I., Crocker M.:: Recurrent networks and natural language: exploiting self-organization. In Proceedings of the 28th Annual Conference of the Cognitive Science Society, Vancouver, Canada. 1275-1280. 2006.pdfbib
  • Farkaš I.: Samoorganizácia ako hybná sila dynamických vzorcov aktivít v mozgu a mysli. In J. Kelemen J. and V. Kvasnicka (eds.), Kognícia a umelý život VI, Třešť, Česká republika. 143-148. 2006.pdfbib
  • Tiňo P., Farkaš I., van Mourik J.: Dynamics and topographic organization of recursive self-organizing maps. Neural Computation 182529-2567. 2006.pdfbib
  • Tiňo P., Farkaš I., van Mourik J.: Recursive self-organizing map as a contractive iterative function system. In M. Gallagher, J. Hogan, F. Maire (eds.), Intelligent Data Engineering and Automated Learning - IDEAL 2005, Lecture Notes in Computer Science, Springer. 327-334. 2005.pdfbib
  • Tiňo P., Farkaš I.: On non-Markovian topographic organization of receptive fields in recursive self-organizing map. In L. Wang, K. Chen, Y.S. Ong. (eds.), Advances in Natural Computation - ICNC 2005, Lecture Notes in Computer Science, Springer. 676-685. 2005.pdfbib
  • Farkaš I.: Recipročná kauzalita medzi mysľou a mozgom z neurovednej perspektívy. In J. Kelemen, V. Kvasnicka, J. Pospichal (eds.), Kognícia a umelý život V, Smolenice, Slovakia. 117-124. 2005.pdfbib
  • Farkaš I.: Konekcionistické modelovanie jazyka. In J. Rybar, V. Kvasnicka, I. Farkas (eds.), Jazyk a kognícia, Kalligram, Bratislava. 262-305. 2005.pdfbib
  • Farkaš I.: Súboj symbolov a pravdepodobností. Anthropos 2(1). 69-74. 2005.bib
  • Rybár J., Kvasnička V., Farkaš I.: Kognitívny prístup ku skúmaniu jazyka. 2005.bib
  • Li P., Farkaš I., MacWhinney B.: Early lexical development in a self-organizing neural network. Neural Networks 17(8-9). 1345-1362. 2004.pdfbib
  • Farkaš I.: What is the structure of human lexical system?. In Sincak P. et al. (eds.), Cognition and Artificial Life III, Stara Lesna, Slovakia. 13-18. 2003.pdfbib
  • Farkaš I.: Lexical acquisition and developing semantic map. Neural Network World 13(3). 235-245. 2003.pdfbib
  • Farkaš I., Li P.: Modeling the development of lexicon with a growing self-organizing map. In Caulfield, H.J. et al. (eds.), Proceedings of the 6th Joint Conference on Information Sciences, Research Triangle Park, NC. 553-556. 2002.pdfbib
  • Li P., Farkaš I.: A self-organizing connectionist model of bilingual processing. In R. Heredia & J. Altarriba (eds.), Bilingual Sentence Processing, North-Holland: Elsevier Science Publisher. 59-85. 2002.pdfbib
  • Farkaš I., Li P.: DevLex: A self-organizing neural network model of the development of lexicon. In International Conference on Neural Information Processing (ICONIP), Singapore. 2002.pdfbib
  • Farkaš I., Li P.: A self-organizing neural network model of the acquisition of word meaning. In E. Altmann, A. Cleeremans, C. Schunn, & W. Gray (eds.), Proceedings of the 4th International Conference on Cognitive Modeling, Fairfax, VA. 67-72. 2001.pdfbib
  • Farkaš I.: Self-organizing map for representing structures. In Sincak P. et al. (eds.), The State of the Art in Computational Intelligence (Proceedings of European Symposium on Computational Intelligence), Kosice, Slovakia, Springer-Verlag. 25-31. 2000.pdfbib
  • Farkaš I.: Jazyk, mozog a evolúcia. In Kognitívne vedy III, Bratislava. 45-55. 2000.pdfbib
  • Chudý L., Farkaš I.: Regionálna analýza pomocou samoorganizujúcich sa máp. Politická ekonomie 48(5). 685-697. 2000.bib
  • Chudý L., Farkaš I.: Modely horizontálneho regionálneho finančného vyrovnávania. Ekonomický časopis 48(5). 634-649. 2000.bib
  • Farkaš I., Miikkulainen R.: Modeling the self-organization of directional selectivity in the primary visual cortex. In Proceedings of ICANN'99, Edinburgh, Scotland. 251-256. 1999.pdfbib
  • Chudý L., Farkaš I.: Prediction of chaotic time-series using dynamic cell structures and local linear models. Neural Network World 8(5). 481-489. 1998.pdfbib
  • Rosipal R., Koska M., Farkaš I.: Prediction of chaotic time-series with a resource-allocating RBF network. Neural Processing Letters 71-13. 1998.pdfbib
  • Farkaš I.: Invariance of Gaussian-vector mapping using a self-organizing map. Neural Network World 7(2). 153-159. 1997.pdfbib
  • Farkaš I.: Samoorganizujúce sa mapy. In V. Kvasnicka, L. Benuskova, J. Pospichal, I. Farkas, P. Tino, A. Kral (eds.), Úvod do teórie neurónových sietí, IRIS, Bratislava. 142-189. 1997.pdfbib
  • Farkaš I., Chudý L.: Application of a growing self-organizing map to thinning of binary characters with noise. In Proceedings of WSOM'97: Workshop on Self-Organizing Maps, Espoo, Finland. 215-219. 1997.pdfbib
  • Farkaš I., Chudý L.: Skeletonization of binary patterns with modified dynamic cell structures.. In Frollo, I. and Plackova, A. (eds.), Measurement'97, Smolenice, Slovakia, Polygraphy of SAS Bratislava. 258-261. 1997.pdfbib
  • Rosipal R., Koska M., Farkaš I.: Chaotic time-series prediction using resource-allocating RBF networks. In Frollo, I. and Plackova, A. (eds.), Measurement'97, Smolenice, Slovakia, Polygraphy of SAS Bratislava. 282-285. 1997.pdfbib
  • Farkaš I., Chudý L.: Modified dynamic cell structures as a thinning algorithm. In Sincak P. (eds.), Proc. of the First Slovak Symposium on Neural Networks, Herlany, ELFA. 71-79. 1996.pdfbib
  • Farkaš I.: Self-organized formant mapping. Neural Network World 5(3). 287-297. 1995.bib
  • Farkaš I.: Interference cancelling using constrained topological mapping. Neural Network World 3(2). 121-130. 1993.bib
  • to the top