Lehel Csató

According to our database, Lehel Csató authored at least 37 papers between 1999 and 2023.

Collaborative distances:

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

2023

Evaluating cooperative-competitive dynamics with deep Q-learning.

Anikó Kopacz, Lehel Csató, Camelia Chira

Neurocomputing, 2023

Wavelet-Based Prototype Networks.

Tamás Kaszta, Hanna-Georgina Lieb, Lehel Csató

Proceedings of the 21st IEEE Jubilee International Symposium on Intelligent Systems and Informatics, 2023

2022

Standardized feature extraction from pairwise conflicts applied to the train rescheduling problem.

Anikó Kopacz, Ágnes Mester, Sándor Kolumbán, Lehel Csató

CoRR, 2022

Neural Network Pruning based on Filter Importance Values Approximated with Monte Carlo Gradient Estimation.

Csanád Sándor, Szabolcs Pável, Lehel Csató

Proceedings of the 17th International Joint Conference on Computer Vision, 2022

Applying Deep Q-learning for Multi-agent Cooperative-Competitive Environments.

Anikó Kopacz, Lehel Csató, Camelia Chira

Proceedings of the 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022), 2022

2021

Active Learning with Bayesian UNet for Efficient Semantic Image Segmentation.

Isah Charles Saidu, Lehel Csató

J. Imaging, 2021

2020

Pruning CNN's with Linear Filter Ensembles.

Csanád Sándor, Szabolcs Pável, Lehel Csató

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019

Single View Distortion Correction using Semantic Guidance.

Szabolcs-Botond Lorincz, Szabolcs Pável, Lehel Csató

Proceedings of the International Joint Conference on Neural Networks, 2019

Distortion Estimation Through Explicit Modeling of the Refractive Surface.

Szabolcs Pável, Csanád Sándor, Lehel Csató

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

2017

Finding Patterns in Visualizations of Programs.

Catalin F. Perticas, Bipin Indurkhya, Razvan V. Florian, Lehel Csató

Proceedings of the 28th Annual Workshop of the Psychology of Programming Interest Group, 2017

2014

Linear spectral hashing.

Zalán Bodó, Lehel Csató

Neurocomputing, 2014

Indirect robot model learning for tracking control.

Botond Attila Bócsi, Lehel Csató, Jan Peters

Adv. Robotics, 2014

Simulation-Extrapolation Gaussian Processes for Input Noise Modeling.

Botond Bocsi, Hunor Jakab, Lehel Csató

Proceedings of the 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2014

Augmented hashing for semi-supervised scenarios.

Zalán Bodó, Lehel Csató

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

2013

Alignment-based transfer learning for robot models.

Botond Bocsi, Lehel Csató, Jan Peters

Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Novel Feature Selection and Kernel-Based Value Approximation Method for Reinforcement Learning.

Hunor Sandor Jakab, Lehel Csató

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

Hessian Corrected Input Noise Models.

Botond Attila Bócsi, Lehel Csató

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

2012

Reinforcement learning with guided policy search using Gaussian processes.

Hunor Jakab, Lehel Csató

Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Improving kernel locality-sensitive hashing using pre-images and bounds.

Zalán Bodó, Lehel Csató

Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Learning tracking control with forward models.

Botond Bocsi, Philipp Hennig, Lehel Csató, Jan Peters

Proceedings of the IEEE International Conference on Robotics and Automation, 2012

Manifold-based non-parametric learning of action-value functions.

Hunor Jakab, Lehel Csató

Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

2011

Active Learning with Clustering.

Zalán Bodó, Zsolt Minier, Lehel Csató

Proceedings of the Active Learning and Experimental Design workshop, 2011

Projected sequential Gaussian processes: A C++ tool for interpolation of large datasets with heterogeneous noise.

Remi Louis Barillec, Ben Ingram, Dan Cornford, Lehel Csató

Comput. Geosci., 2011

Learning inverse kinematics with structured prediction.

Botond Bocsi, Duy Nguyen-Tuong, Lehel Csató, Bernhard Schölkopf, Jan Peters

Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011

Improving Gaussian Process Value Function Approximation in Policy Gradient Algorithms.

Hunor Jakab, Lehel Csató

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

2010

Hierarchical and Reweighting Cluster Kernels for Semi-Supervised Learning.

Zalán Bodó, Lehel Csató

Int. J. Comput. Commun. Control, 2010

2009

Bayesian Network Classifier for Medical Data Analysis.

Beáta Reiz, Lehel Csató

Int. J. Comput. Commun. Control, 2009

Dirichlet process-based component detection in state-space models.

Botond Bocsi, Lehel Csató

Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

2008

Prufer Number Encoding for Genetic Bayesian Network Structure Learning Algorithm.

Beáta Reiz, Lehel Csató, Dan Dumitrescu

Proceedings of the SYNASC 2008, 2008

2007

Wikipedia-Based Kernels for Text Categorization.

Zsolt Minier, Zalán Bodó, Lehel Csató

Proceedings of the Ninth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2007

Kernel PCA based clustering for inducing features in text categorization.

Zsolt Minier, Lehel Csató

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

2003

Tractable inference for probabilistic data models.

Lehel Csató, Manfred Opper, Ole Winther

Complex., 2003

2002

Sparse On-Line Gaussian Processes.

Lehel Csató, Manfred Opper

Neural Comput., 2002

2001

TAP Gibbs Free Energy, Belief Propagation and Sparsity.

Lehel Csató, Manfred Opper, Ole Winther

Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Online Approximations for Wind-Field Models.

Lehel Csató, Dan Cornford, Manfred Opper

Proceedings of the Artificial Neural Networks, 2001

2000

Sparse Representation for Gaussian Process Models.

Lehel Csató, Manfred Opper

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

1999

Efficient Approaches to Gaussian Process Classification.

Lehel Csató, Ernest Fokoué, Manfred Opper, Bernhard Schottky, Ole Winther

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999