Igor Farkas

According to our database, Igor Farkas authored at least 52 papers between 1998 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Self-supervised network distillation: An effective approach to exploration in sparse reward environments.

Matej Pechác, Michal Chovanec, Igor Farkas

Neurocomputing, 2024

RecViT: Enhancing Vision Transformer with Top-Down Information Flow.

Stefan Pócos, Iveta Becková, Igor Farkas

Proceedings of the 19th International Joint Conference on Computer Vision, 2024

Learning Low-Level Causal Relations Using a Simulated Robotic Arm.

Miroslav Cibula, Matthias Kerzel, Igor Farkas

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

2023

Exploration by self-supervised exploitation.

Matej Pechác, Michal Chovanec, Igor Farkas

CoRR, 2023

Appearance-Based Gaze Estimation Enhanced with Synthetic Images Using Deep Neural Networks.

Dmytro Herashchenko, Igor Farkas

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Robot at the Mirror: Learning to Imitate via Associating Self-supervised Models.

Andrej Lúcny, Kristína Malinovská, Igor Farkas

Proceedings of the Artificial Neural Networks and Machine Learning, 2023

Safe Reinforcement Learning in a Simulated Robotic Arm.

Luka Kovac, Igor Farkas

Proceedings of the Artificial Neural Networks and Machine Learning, 2023

2022

A connectionist model of associating proprioceptive and tactile modalities in a humanoid robot.

Kristína Malinovská, Igor Farkas, Jana Harvanová, Matej Hoffmann

Proceedings of the IEEE International Conference on Development and Learning, 2022

Examining the Proximity of Adversarial Examples to Class Manifolds in Deep Networks.

Stefan Pócos, Iveta Becková, Igor Farkas

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

2021

Semi-supervised Learning in Camera Surveillance Image Classification.

Matús Tuna, Kristína Malinovská, Igor Farkas, Svatopluk Kraus, Pavel Krsek

Proceedings of the 17th IEEE International Conference on Intelligent Computer Communication and Processing, 2021

Intrinsic Motivation Model Based on Reward Gating.

Matej Pechác, Igor Farkas

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

Generative Properties of Universal Bidirectional Activation-Based Learning.

Kristína Malinovská, Igor Farkas

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

Advances in Adaptive Skill Acquisition.

Juraj Holas, Igor Farkas

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

2020

Assessment of Manifold Unfolding in Trained Deep Neural Network Classifiers.

Stefan Pócos, Iveta Becková, Tomás Kuzma, Igor Farkas

Proceedings of the Trustworthy AI - Integrating Learning, Optimization and Reasoning, 2020

Adaptive Skill Acquisition in Hierarchical Reinforcement Learning.

Juraj Holas, Igor Farkas

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

Computational Analysis of Robustness in Neural Network Classifiers.

Iveta Becková, Stefan Pócos, Igor Farkas

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

2019

Echo State Networks with Artificial Astrocytes and Hebbian Connections.

Peter Gergel, Igor Farkas

Proceedings of the Advances in Computational Intelligence, 2019

Modeling Self-organized Emergence of Perspective In/variant Mirror Neurons in a Robotic System.

Jakub Pospíchal, Igor Farkas, Matej Pechác, Kristína Malinovská

Proceedings of the Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics, 2019

Embedding Complexity of Learned Representations in Neural Networks.

Tomas Kuzma, Igor Farkas

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning, 2019

UBAL: a Universal Bidirectional Activation-based Learning Rule for Neural Networks.

Kristína Malinovská, Ludovít Malinovský, Pavel Krsek, Svatopluk Kraus, Igor Farkas

Proceedings of the CIIS 2019: The 2nd International Conference on Computational Intelligence and Intelligent Systems, 2019

Experimental Procedure for Evaluation of Visuospatial Cognitive Functions Training in Virtual Reality.

Stefan Korecko, Branislav Sobota, Marián Hudák, Igor Farkas, Barbora Cimrová, Peter Vasil, Dominik Trojcák

Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019, 2019

2018

Robotic Homunculus: Learning of Artificial Skin Representation in a Humanoid Robot Motivated by Primary Somatosensory Cortex.

Matej Hoffmann, Zdenek Straka, Igor Farkas, Michal Vavrecka, Giorgio Metta

IEEE Trans. Cogn. Dev. Syst., 2018

Computational model of enactive visuospatial mental imagery using saccadic perceptual actions.

Jan Jug, Tine Kolenik, André Ofner, Igor Farkas

Cogn. Syst. Res., 2018

Evaluation of Information-Theoretic Measures in Echo State Networks on the Edge of Stability.

Miloslav Torda, Igor Farkas

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Computational Analysis of Learned Representations in Deep Neural Network Classifiers.

Tomas Kuzma, Igor Farkas

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Towards More Biologically Plausible Error-Driven Learning for Artificial Neural Networks.

Kristína Malinovská, Ludovít Malinovský, Igor Farkas

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Investigating the Role of Astrocyte Units in a Feedforward Neural Network.

Peter Gergel, Igor Farkas

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Assessment and training of visuospatial cognitive functions in virtual reality: proposal and perspective.

Stefan Korecko, Marián Hudák, Branislav Sobota, Martin Marko, Barbora Cimrová, Igor Farkas, Roman Rosipal

Proceedings of the 9th IEEE International Conference on Cognitive Infocommunications, 2018

2017

Maximizing memory capacity of echo state networks with orthogonalized reservoirs.

Igor Farkas, Peter Gergel

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016

Computational analysis of memory capacity in echo state networks.

Igor Farkas, Radomír Bosák, Peter Gergel

Neural Networks, 2016

2015

Computational analysis of the Bidirectional Activation-based Learning in autoencoder task.

Peter Csiba, Igor Farkas

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Connectionist Modeling of Part-Whole Analogy Learning.

Peter Gergel, Igor Farkas

Proceedings of the EuroAsianPacific Joint Conference on Cognitive Science / 4th European Conference on Cognitive Science / 11th International Conference on Cognitive Science, 2015

2014

A Multimodal Connectionist Architecture for Unsupervised Grounding of Spatial Language.

Michal Vavrecka, Igor Farkas

Cogn. Comput., 2014

Memory Capacity of Input-Driven Echo State Networks at the Edge of Chaos.

Peter Barancok, Igor Farkas

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

Calculation of object position in various reference frames with a robotic simulator.

Marcel Svec, Igor Farkas

Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 2014

2013

Towards a robotic model of the mirror neuron system.

Kristína Rebrová, Matej Pechác, Igor Farkas

Proceedings of the 2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics, 2013

Bidirectional Activation-based Neural Network Learning Algorithm.

Igor Farkas, Kristína Rebrová

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2013, 2013

2012

Grounding the Meanings in Sensorimotor Behavior using Reinforcement Learning.

Igor Farkas, Tomás Malík, Kristína Rebrová

Frontiers Neurorobotics, 2012

2011

Bio-inspired Model of Spatial Cognition.

Michal Vavrecka, Igor Farkas, Lenka Lhotská

Proceedings of the Neural Information Processing - 18th International Conference, 2011

Modeling Utterance-mediated Attention in Situated Language Comprehension.

Jan Svantner, Igor Farkas, Matthew W. Crocker

Proceedings of the 33th Annual Meeting of the Cognitive Science Society, 2011

2010

Experimental comparison of recursive self-organizing maps for processing tree-structured data.

Pavol Vanco, Igor Farkas

Neurocomputing, 2010

2009

Segmentation and supervised classification of image objects in Epo doping-control.

Ivan Bajla, Frantisek Rublík, Barbora Arendacká, Igor Farkas, Klára Hornisová, Svorad Stolc, Viktor Witkovský

Mach. Vis. Appl., 2009

Recursive Self-organizing Networks for Processing Tree Structures - Empirical Comparison.

Pavol Vanco, Igor Farkas

Proceedings of the IJCCI 2009, 2009

2008

Syntactic systematicity in sentence processing with a recurrent self-organizing network.

Igor Farkas, Matthew W. Crocker

Neurocomputing, 2008

Learning Nonadjacent Dependencies with a Recurrent Neural Network.

Igor Farkas

Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

2007

Systematicity in sentence processing with a recursive self-organizing neural network.

Igor Farkas, Matthew W. Crocker

Proceedings of the 15th European Symposium on Artificial Neural Networks, 2007

2006

Dynamics and Topographic Organization of Recursive Self-Organizing Maps.

Peter Tiño, Igor Farkas, Jort van Mourik

Neural Comput., 2006

2005

Recursive Self-organizing Map as a Contractive Iterative Function System.

Peter Tiño, Igor Farkas, Jort van Mourik

Proceedings of the Intelligent Data Engineering and Automated Learning, 2005

On Non-markovian Topographic Organization of Receptive Fields in Recursive Self-organizing Map.

Peter Tiño, Igor Farkas

Proceedings of the Advances in Natural Computation, First International Conference, 2005

2004

Early lexical development in a self-organizing neural network.

Ping Li, Igor Farkas, Brian MacWhinney

Neural Networks, 2004

2002

Modeling the Development of Lexicon with a Growing Self-Organizing Map.

Igor Farkas, Ping Li

Proceedings of the 6th Joint Conference on Information Science, 2002

1998

Prediction of Chaotic Time-Series with a Resource-Allocating RBF Network.

Roman Rosipal, Milos Koska, Igor Farkas

Neural Process. Lett., 1998