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.
Pecháč M., Chovanec M., Farkaš I.: Self-supervised network distillation: An effective approach to exploration in sparse reward environments. Neurocomputing 2024.
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.
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.
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].
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.
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.
Farkaš I.: Dôveryhodnost’ výpočtových modelov v umelej inteligencii a robotike. In Kognícia a umelý život XXI, Smolenice, Vydavateľstvo UK v Bratislave. 28-29. 2023.
Farkaš, I., Ballová Mikušková, E., Takáč, M., Malinovská, K., Fandl, M.: Kognícia a umelý život 2023. Univerzita Komenského v Bratislave. 2023.
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.
Reinboth T., Farkaš I.: Ultimate grounding of abstract concepts: A graded account. Journal of Cognition, 5(1). 2022.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Farkaš I., Masulli P., Wermter S. (eds.): Artificial Neural Networks and Machine Learning - ICANN 2020, part I. Springer Nature Switzerland AG. 2020.
Farkaš I., Masulli P., Wermter S. (eds.): Artificial Neural Networks and Machine Learning - ICANN 2020, part II. Springer Nature Switzerland AG. 2020.
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.
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.
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.
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.
Farkaš I., Takáč M, Gergeľ P., Tomko M. (eds.): Kognícia a umelý život XIX. Univerzita Komenského v Bratislave. 2019.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Farkaš I.: On abstraction: psychological, neural, and computational perspectives. In Kognice a umělý život (KUZ). 2016.
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.
Farkaš I., Bosák R., Gergeľ P.: Computational analysis of memory capacity in echo state networks. Neural Networks 83, 109-120. 2016.
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.
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.
Kuzma T., Farkaš I.: Automatická tvorba učebných plánov pre strojové učenie. In Kognícia a umelý život XV, Vydavateľstvo Univerzity Komenského, Bratislava. 99-102. 2015.
Farkaš, I., Takáč, M., Rybár, J., Kelemen, J. (eds.): Kognícia a umelý život XV. Univerzita Komenského v Bratislave, Bratislava. 2015.
Gergeľ P., Farkaš I.: Connectionist modeling of part–whole analogy learning. In Proceedings of the EuroAsianPacific Joint Conference on Cognitive Science. 587-592. 2015.
Vavrečka M., Farkaš I.: A multimodal connectionist architecture for unsupervised grounding of spatial language. Cognitive Computation 6:101-112. 2014.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Švantner J., Farkaš I., Crocker M.: Modeling utterance-mediated visual attention during situated comprehension. Neural Network World 22(2). 85-101. 2012.
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.
Farkaš I.: Indispensability of computational modeling in cognitive science. Journal of Cognitive Science 13,401-435. 2012.
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.
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.
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.
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.
Farkaš I., Malý M., Rebrová K.: Mirror neurons – theoretical and computational issues. Technical report TR-2011-028. Comenius University in Bratislava. 2011.
Vavrečka M., Farkaš I., Lhotská L.: Bio-inspired model of spatial cognition. In International Conference on Neural Information Processing (ICONIP). 2011.
Farkaš I.: Konekcionizmus v náručí výpočtovej kognitívnej vedy. In Kvasnička V. et al. (eds.), Umelá inteligencia a kognitívna veda III. 19-62. 2011.
Šilar J., Kokoška M., Rebrová K., Farkaš I.: Motor resonance based desynchronization of the EEG mu rhythm. Activitas Nervosa Superior Rediviva 53 2011. Abstract.
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.
Vančo P., Farkaš I.: Experimental comparison of recursive self-organizing maps for processing tree-structured data. Neurocomputing 73 1362-1375. 2010.
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.
Farkaš I.: Mental causation in a physical brain?. In Brain-Inspired Cognitive Systems, Universidad Politécnica de Madrid. 14-16 July 2010.
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.
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.
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.
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.
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.
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.
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.
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.
Farkaš I., Crocker M.: Syntactic systematicity in sentence processing with a recurrent self-organizing network. Neurocomputing 711172-1179. 2008.
Farkaš I.: Konceptuálne východiská pre model stelesnenej mysle. In Kvasnička V., Kelemen J., Pospichal J. (eds.), Modely mysle, Vydavateľstvo Európa, Bratislava. 35-64. 2008.
Šefránek, J., Takáč, M., Farkaš, I.: Vznik inteligencie v umelých systémoch. In Magdolen, D. (eds.), Hmota, život, inteligencia: Vznik, VEDA, Bratislava. 245-270. 2008.
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.
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.
Farkaš I., Vančo P.: Spracovanie postupností symbolov pomocou rekurzívnych neurónových máp. In Kognícia a umelý život VII, Slezská univerzita, Opava. 99-106. 2007.
Farkaš I., Švantner J.: Učenie nesusedných závislostí pomocou rekurentných neurónových sietí. In Kognícia a umelý život VII, Slezská univerzita, Opava. 389-394. 2007.
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.
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.
Tiňo P., Farkaš I., van Mourik J.: Dynamics and topographic organization of recursive self-organizing maps. Neural Computation 182529-2567. 2006.
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.
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.
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.
Farkaš I.: Konekcionistické modelovanie jazyka. In J. Rybar, V. Kvasnicka, I. Farkas (eds.), Jazyk a kognícia, Kalligram, Bratislava. 262-305. 2005.
Farkaš I.: Súboj symbolov a pravdepodobností. Anthropos 2(1). 69-74. 2005.
Rybár J., Kvasnička V., Farkaš I.: Kognitívny prístup ku skúmaniu jazyka. 2005.
Li P., Farkaš I., MacWhinney B.: Early lexical development in a self-organizing neural network. Neural Networks 17(8-9). 1345-1362. 2004.
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.
Farkaš I.: Lexical acquisition and developing semantic map. Neural Network World 13(3). 235-245. 2003.
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.
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.
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.
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.
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.
Farkaš I.: Jazyk, mozog a evolúcia. In Kognitívne vedy III, Bratislava. 45-55. 2000.
Chudý L., Farkaš I.: Regionálna analýza pomocou samoorganizujúcich sa máp. Politická ekonomie 48(5). 685-697. 2000.
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.
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.
Rosipal R., Koska M., Farkaš I.: Prediction of chaotic time-series with a resource-allocating RBF network. Neural Processing Letters 71-13. 1998.
Farkaš I.: Invariance of Gaussian-vector mapping using a self-organizing map. Neural Network World 7(2). 153-159. 1997.
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.
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.
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.
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.
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.
