Igor Farkas

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 33

Top Topics

Object Position

Skill Acquisition

Memory Capacity

Top Venues

Publications

Stefan Pócos, Iveta Becková, Igor Farkas
RecViT: Enhancing Vision Transformer with Top-Down Information Flow. VISIGRAPP (3): VISAPP (2024)
Matej Pechác, Michal Chovanec, Igor Farkas
Self-supervised network distillation: An effective approach to exploration in sparse reward environments. Neurocomputing 599 (2024)
Luka Kovac, Igor Farkas
Safe Reinforcement Learning in a Simulated Robotic Arm. CoRR (2023)
Dmytro Herashchenko, Igor Farkas
Appearance-Based Gaze Estimation Enhanced with Synthetic Images Using Deep Neural Networks. SSCI (2023)
Andrej Lúcny, Kristína Malinovská, Igor Farkas
Robot at the Mirror: Learning to Imitate via Associating Self-supervised Models. CoRR (2023)
Dmytro Herashchenko, Igor Farkas
Appearance-based gaze estimation enhanced with synthetic images using deep neural networks. CoRR (2023)
Matej Pechác, Michal Chovanec, Igor Farkas
Exploration by self-supervised exploitation. CoRR (2023)
Kristína Malinovská, Igor Farkas, Jana Harvanová, Matej Hoffmann
A connectionist model of associating proprioceptive and tactile modalities in a humanoid robot. ICDL (2022)
Stefan Pócos, Iveta Becková, Igor Farkas
Examining the Proximity of Adversarial Examples to Class Manifolds in Deep Networks. ICANN (4) (2022)
Stefan Pócos, Iveta Becková, Igor Farkas
Examining the Proximity of Adversarial Examples to Class Manifolds in Deep Networks. CoRR (2022)
Juraj Holas, Igor Farkas
Advances in Adaptive Skill Acquisition. ICANN (4) (2021)
Matús Tuna, Kristína Malinovská, Igor Farkas, Svatopluk Kraus, Pavel Krsek
Semi-supervised Learning in Camera Surveillance Image Classification. ICCP (2021)
Matej Pechác, Igor Farkas
Intrinsic Motivation Model Based on Reward Gating. ICANN (4) (2021)
Kristína Malinovská, Igor Farkas
Generative Properties of Universal Bidirectional Activation-Based Learning. ICANN (3) (2021)
Juraj Holas, Igor Farkas
Adaptive Skill Acquisition in Hierarchical Reinforcement Learning. ICANN (2) (2020)
Stefan Pócos, Iveta Becková, Tomás Kuzma, Igor Farkas
Assessment of Manifold Unfolding in Trained Deep Neural Network Classifiers. TAILOR (2020)
Iveta Becková, Stefan Pócos, Igor Farkas
Computational Analysis of Robustness in Neural Network Classifiers. ICANN (1) (2020)
Kristína Malinovská, Ludovít Malinovský, Pavel Krsek, Svatopluk Kraus, Igor Farkas
UBAL: a Universal Bidirectional Activation-based Learning Rule for Neural Networks. CIIS (2019)
Jakub Pospíchal, Igor Farkas, Matej Pechác, Kristína Malinovská
Modeling Self-organized Emergence of Perspective In/variant Mirror Neurons in a Robotic System. ICDL-EPIROB (2019)
Stefan Korecko, Branislav Sobota, Marián Hudák, Igor Farkas, Barbora Cimrová, Peter Vasil, Dominik Trojcák
Experimental Procedure for Evaluation of Visuospatial Cognitive Functions Training in Virtual Reality. AISI (2019)
Peter Gergel, Igor Farkas
Echo State Networks with Artificial Astrocytes and Hebbian Connections. IWANN (1) (2019)
Tomas Kuzma, Igor Farkas
Embedding Complexity of Learned Representations in Neural Networks. ICANN (2) (2019)
Peter Gergel, Igor Farkas
Investigating the Role of Astrocyte Units in a Feedforward Neural Network. ICANN (3) (2018)
Stefan Korecko, Marián Hudák, Branislav Sobota, Martin Marko, Barbora Cimrová, Igor Farkas, Roman Rosipal
Assessment and training of visuospatial cognitive functions in virtual reality: proposal and perspective. CogInfoCom (2018)
Miloslav Torda, Igor Farkas
Evaluation of Information-Theoretic Measures in Echo State Networks on the Edge of Stability. IJCNN (2018)
Kristína Malinovská, Ludovít Malinovský, Igor Farkas
Towards More Biologically Plausible Error-Driven Learning for Artificial Neural Networks. ICANN (3) (2018)
Jan Jug, Tine Kolenik, André Ofner, Igor Farkas
Computational model of enactive visuospatial mental imagery using saccadic perceptual actions. Cogn. Syst. Res. 49 (2018)
Tomas Kuzma, Igor Farkas
Computational Analysis of Learned Representations in Deep Neural Network Classifiers. IJCNN (2018)
Matej Hoffmann, Zdenek Straka, Igor Farkas, Michal Vavrecka, Giorgio Metta
Robotic Homunculus: Learning of Artificial Skin Representation in a Humanoid Robot Motivated by Primary Somatosensory Cortex. IEEE Trans. Cogn. Dev. Syst. 10 (2) (2018)
Igor Farkas, Peter Gergel
Maximizing memory capacity of echo state networks with orthogonalized reservoirs. IJCNN (2017)
Igor Farkas, Radomír Bosák, Peter Gergel
Computational analysis of memory capacity in echo state networks. Neural Networks 83 (2016)
Peter Csiba, Igor Farkas
Computational analysis of the Bidirectional Activation-based Learning in autoencoder task. IJCNN (2015)
Peter Gergel, Igor Farkas
Connectionist Modeling of Part-Whole Analogy Learning. EAPCogSci (2015)
Marcel Svec, Igor Farkas
Calculation of object position in various reference frames with a robotic simulator. CogSci (2014)
Michal Vavrecka, Igor Farkas
A Multimodal Connectionist Architecture for Unsupervised Grounding of Spatial Language. Cogn. Comput. 6 (1) (2014)
Peter Barancok, Igor Farkas
Memory Capacity of Input-Driven Echo State Networks at the Edge of Chaos. ICANN (2014)
Kristína Rebrová, Matej Pechác, Igor Farkas
Towards a robotic model of the mirror neuron system. ICDL-EPIROB (2013)
Igor Farkas, Kristína Rebrová
Bidirectional Activation-based Neural Network Learning Algorithm. ICANN (2013)
Igor Farkas, Tomás Malík, Kristína Rebrová
Grounding the Meanings in Sensorimotor Behavior using Reinforcement Learning. Frontiers Neurorobotics 6 (2012)
Jan Svantner, Igor Farkas, Matthew W. Crocker
Modeling Utterance-mediated Attention in Situated Language Comprehension. CogSci (2011)
Michal Vavrecka, Igor Farkas, Lenka Lhotská
Bio-inspired Model of Spatial Cognition. ICONIP (1) (2011)
Pavol Vanco, Igor Farkas
Experimental comparison of recursive self-organizing maps for processing tree-structured data. Neurocomputing 73 (7-9) (2010)
Ivan Bajla, Frantisek Rublík, Barbora Arendacká, Igor Farkas, Klára Hornisová, Svorad Stolc, Viktor Witkovský
Segmentation and supervised classification of image objects in Epo doping-control. Mach. Vis. Appl. 20 (4) (2009)
Pavol Vanco, Igor Farkas
Recursive Self-organizing Networks for Processing Tree Structures - Empirical Comparison. IJCCI (2009)
Igor Farkas, Matthew W. Crocker
Syntactic systematicity in sentence processing with a recurrent self-organizing network. Neurocomputing 71 (7-9) (2008)
Igor Farkas
Learning Nonadjacent Dependencies with a Recurrent Neural Network. ICONIP (2) (2008)
Igor Farkas, Matthew W. Crocker
Systematicity in sentence processing with a recursive self-organizing neural network. ESANN (2007)
Peter Tiño, Igor Farkas, Jort van Mourik
Dynamics and Topographic Organization of Recursive Self-Organizing Maps. Neural Comput. 18 (10) (2006)
Peter Tiño, Igor Farkas, Jort van Mourik
Recursive Self-organizing Map as a Contractive Iterative Function System. IDEAL (2005)
Peter Tiño, Igor Farkas
On Non-markovian Topographic Organization of Receptive Fields in Recursive Self-organizing Map. ICNC (2) (2005)
Ping Li, Igor Farkas, Brian MacWhinney
Early lexical development in a self-organizing neural network. Neural Networks 17 (8-9) (2004)
Igor Farkas, Ping Li
Modeling the Development of Lexicon with a Growing Self-Organizing Map. JCIS (2002)
Roman Rosipal, Milos Koska, Igor Farkas
Prediction of Chaotic Time-Series with a Resource-Allocating RBF Network. Neural Process. Lett. 7 (3) (1998)